Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/getvmio/free-machine-learning-resources

[Machine Learning Free Resources] This repository collects 212 of free resources for Machine Learning. 🤖 Unlock the potential of intelligent systems with our Machine Learning Lab repository! Featuring a curated collection of free resources and an online Playground, this is your experimental groun...
https://github.com/getvmio/free-machine-learning-resources

List: free-machine-learning-resources

awesome-list free-resources getvm machine-learning playground programming

Last synced: about 1 month ago
JSON representation

[Machine Learning Free Resources] This repository collects 212 of free resources for Machine Learning. 🤖 Unlock the potential of intelligent systems with our Machine Learning Lab repository! Featuring a curated collection of free resources and an online Playground, this is your experimental groun...

Awesome Lists containing this project

README 

        
# Machine Learning Free Resources



🤖 Unlock the potential of intelligent systems with our Machine Learning Lab repository! Featuring a curated collection of free resources and an online Playground, this is your experimental ground for exploring cutting-edge ML techniques and gaining practical experience in this transformative field.



## Resources



|   Index | Name                                                                                                                                                                                      | Category            | Description                                                                                                                                                                                                                                                                |

|---------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|

|       1 | [Machine Learning Tutorials](https://getvm.io/tutorials/machine-learning-tutorials)                                                                                                       | Technical Tutorials | Learn core machine learning concepts, algorithms, and techniques using Python and popular libraries like Scikit-learn and TensorFlow. Explore supervised, unsupervised, and neural network methods.                                                                        |

|       2 | [Data Science Tutorials](https://getvm.io/tutorials/data-science-tutorials)                                                                                                               | Technical Tutorials | Comprehensive data science course covering Python, statistics, machine learning, data engineering, and real-world problem-solving. Become a proficient data scientist.                                                                                                     |

|       3 | [Advanced Artificial Intelligence](https://getvm.io/tutorials/cs-6700-advanced-artificial-intelligence-cornell-university)                                                                | University Courses  | Explore cutting-edge topics in AI, including Watson, human computation, deep learning, and the future of self-driving cars. Ideal for students and professionals seeking the latest AI advancements.                                                                       |

|       4 | [Artificial Intelligence](https://getvm.io/tutorials/cs-188-introduction-to-artificial-intelligence-uc-berkeley)                                                                          | University Courses  | Explore the foundations of intelligent computer systems with this comprehensive AI course from UC Berkeley. Build autonomous agents, learn inference techniques, and master machine learning algorithms.                                                                   |

|       5 | [UvA Deep Learning Course](https://getvm.io/tutorials/uva-deep-learning-course)                                                                                                           | University Courses  | Comprehensive course on the theory and applications of deep learning, with a focus on computer vision and language modelling. Taught by experienced faculty from the University of Amsterdam.                                                                              |

|       6 | [Practical RL](https://getvm.io/tutorials/practical-rl-reinforcement-learning-in-the-wild-yandex-sda)                                                                                     | University Courses  | A practical and hands-on course on reinforcement learning, covering essential tricks and heuristics for solving real-world RL problems.                                                                                                                                    |

|       7 | [Information Retrieval](https://getvm.io/tutorials/cs276-information-retrieval-and-web-search-stanford-university)                                                                        | University Courses  | Comprehensive course covering fundamental concepts and advanced techniques in information retrieval and web search, including indexing, retrieval models, text mining, and more.                                                                                           |

|       8 | [Data Mining](https://getvm.io/tutorials/cs246-mining-massive-data-sets-stanford-university)                                                                                              | University Courses  | Explore data mining and machine learning algorithms for analyzing large-scale data using MapReduce and Spark. Gain hands-on experience in data science and big data analysis.                                                                                              |

|       9 | [Deep Learning](https://getvm.io/tutorials/11-785-deep-learning-carnegie-mellon-university)                                                                                               | University Courses  | Explore the fundamentals of deep learning, from basic concepts to advanced topics, with hands-on experience in PyTorch. Prepare to understand and extend the current literature on deep learning.                                                                          |

|      10 | [Probabilistic Graphical Models](https://getvm.io/tutorials/10-708-probabilistic-graphical-models-carnegie-mellon-university)                                                             | University Courses  | Explore the unified framework of probabilistic graphical models and their applications in AI, statistics, computer systems, and more. Gain a solid foundation for research and problem-solving.                                                                            |

|      11 | [Machine Learning](https://getvm.io/tutorials/10-601-machine-learning-carnegie-mellon-university)                                                                                         | University Courses  | Gain a deep understanding of the theoretical and practical aspects of machine learning, including Bayesian networks, decision tree learning, and Support Vector Machines.                                                                                                  |

|      12 | [Machine Learning: Intro to Statistical Learning](https://getvm.io/tutorials/machine-learning-2014-2015-intro-to-statistical-learning-university-of-oxford)                               | University Courses  | Comprehensive course covering fundamental machine learning concepts and techniques, taught by renowned expert Nando de Freitas. Hands-on practical sessions using Torch deep learning framework.                                                                           |

|      13 | [Introduction to Matrix Methods](https://getvm.io/tutorials/ee103-introduction-to-matrix-methods-stanford-university)                                                                     | University Courses  | Explore the fundamentals of vectors, matrices, and their practical applications in fields like engineering, data science, and finance with this comprehensive course from Stanford University.                                                                             |

|      14 | [Deep Learning for Computer Vision & NLP](https://getvm.io/tutorials/eecs-e6894-deep-learning-for-computer-vision-and-natural-language-processing-columbia-university)                    | University Courses  | Dive into the latest deep learning techniques and their applications in computer vision and natural language processing at this graduate-level research class from Columbia University.                                                                                    |

|      15 | [Big Data Analytics](https://getvm.io/tutorials/eecs-e6893-eecs-e6895-big-data-analytics-advanced-big-data-analytics-columbia-university)                                                 | University Courses  | Gain in-depth knowledge on analyzing Big Data, including storage, processing, analysis, visualization, and application. Ideal for graduate students interested in Big Data and data analysis.                                                                              |

|      16 | [Deep Learning](https://getvm.io/tutorials/ds-ga-1008-deep-learning-new-york-university)                                                                                                  | University Courses  | Dive into the latest advancements in deep learning with this hands-on course from NYU's renowned Data Science Center. Explore cutting-edge techniques in computer vision and natural language processing.                                                                  |

|      17 | [Convex Optimization](https://getvm.io/tutorials/cvx-101-convex-optimization-stanford-university)                                                                                         | University Courses  | Gain a solid foundation in convex optimization and learn practical applications in fields like machine learning, signal processing, and more.                                                                                                                              |

|      18 | [Machine Learning for Data Science](https://getvm.io/tutorials/cs-4786-machine-learning-for-data-science-cornell-university)                                                              | University Courses  | Explore key machine learning concepts and algorithms for data science, including dimensionality reduction, clustering, and probabilistic modeling.                                                                                                                         |

|      19 | [Machine Learning](https://getvm.io/tutorials/cs-4780-machine-learning-cornell-university)                                                                                                | University Courses  | Comprehensive understanding of modern machine learning techniques and their practical applications, including classification, structured models, and hands-on experience.                                                                                                  |

|      20 | [Advanced Robotics](https://getvm.io/tutorials/cs-287-advanced-robotics-uc-berkeley)                                                                                                      | University Courses  | Explore the mathematical foundations and algorithms powering modern robotic systems. Dive into Markov Decision Processes, function approximation, and optimization techniques with broad AI applications.                                                                  |

|      21 | [Convolutional Neural Networks for Visual Recognition](https://getvm.io/tutorials/cs-231n-convolutional-neural-networks-for-visual-recognition-stanford-university)                       | University Courses  | Learn to implement, train and debug your own neural networks for computer vision and deep learning applications.                                                                                                                                                           |

|      22 | [Algorithms for Big Data](https://getvm.io/tutorials/cs-229r-algorithms-for-big-data-harvard-university)                                                                                  | University Courses  | Dive into the theoretical foundations of efficient algorithms for processing big data. Relevant for internet search, machine learning, and scientific computing.                                                                                                           |

|      23 | [Deep Learning for Natural Language Processing](https://getvm.io/tutorials/cs-224d-deep-learning-for-natural-language-processing-stanford-university)                                     | University Courses  | Dive deep into cutting-edge research in deep learning for natural language processing (NLP). Implement, train, and invent your own neural network models for a variety of NLP tasks.                                                                                       |

|      24 | [Introduction to Machine Learning](https://getvm.io/tutorials/cs-189-introduction-to-machine-learning-uc-berkeley)                                                                        | University Courses  | Comprehensive machine learning course covering theoretical foundations, algorithms, and practical applications. Suitable for students with math and computer science background.                                                                                           |

|      25 | [Data Science](https://getvm.io/tutorials/cs-109-data-science-harvard-university)                                                                                                         | University Courses  | Comprehensive introduction to data science, covering data wrangling, analysis, and machine learning. Prepares students for real-world data science challenges.                                                                                                             |

|      26 | [Machine Learning](https://getvm.io/tutorials/coms-4771-machine-learning-columbia-university)                                                                                             | University Courses  | Comprehensive course on machine learning techniques, including generative and discriminative models, taught by an expert professor with hands-on MATLAB implementation.                                                                                                    |

|      27 | [Tensorflow for Deep Learning Research](https://getvm.io/tutorials/cs20si-tensorflow-for-deep-learning-research-stanford-university)                                                      | University Courses  | Learn the fundamentals of TensorFlow for deep learning research. Build models for tasks like word embeddings, translation, and optical character recognition.                                                                                                              |

|      28 | [Deep Learning for Natural Language Processing](https://getvm.io/tutorials/deepnlp-deep-learning-for-natural-language-processing-university-of-oxford)                                    | University Courses  | Dive into the latest advancements in deep learning for NLP, including text analysis, speech recognition, language translation, and more. Gain a solid theoretical foundation and practical experience.                                                                     |

|      29 | [Learn ML Algorithms by coding: Decision Trees](https://getvm.io/tutorials/learn-ml-algorithms-by-coding-decision-trees)                                                                  | Technical Tutorials | Gain a deeper understanding of machine learning algorithms by implementing decision trees from scratch. Suitable for beginners and experienced learners.                                                                                                                   |

|      30 | [A Simple Content-Based Recommendation Engine in Python](https://getvm.io/tutorials/a-simple-content-based-recommendation-engine-in-python)                                               | Technical Tutorials | A practical guide to building a content-based recommendation engine in Python using machine learning techniques. Covers implementation, pros and cons, and production deployment.                                                                                          |

|      31 | [Developing a License Plate Recognition System with Machine Learning in Python](https://getvm.io/tutorials/developing-a-license-plate-recognition-system-with-machine-learning-in-python) | Technical Tutorials | Build a practical license plate recognition system using Python and machine learning. Learn data preprocessing, computer vision, and deep learning algorithms for end-to-end solution development.                                                                         |

|      32 | [How to build a simple artificial neural network with Go](https://getvm.io/tutorials/how-to-build-a-simple-artificial-neural-network-with-go)                                             | Technical Tutorials | Learn how to build a simple artificial neural network using the Go programming language, covering machine learning principles and practical implementation.                                                                                                                |

|      33 | [Python Machine Learning Tutorials](https://getvm.io/tutorials/python-machine-learning-tutorials)                                                                                         | Video Courses       | Comprehensive video series covering the fundamentals of machine learning using Python, with hands-on examples and practical applications.                                                                                                                                  |

|      34 | [Machine Learning Specialization](https://getvm.io/tutorials/machine-learning-specialization)                                                                                             | Video Courses       | Foundational online program on machine learning and AI applications, taught by Andrew Ng of DeepLearning.AI and Stanford Online.                                                                                                                                           |

|      35 | [Deep Learning Fundamentals](https://getvm.io/tutorials/deep-learning-fundamentals)                                                                                                       | Video Courses       | Introductory book on deep learning fundamentals, covering neural networks, convolutional neural networks, recurrent nets, autoencoders, and deep learning use cases.                                                                                                       |

|      36 | [Exploring Fairness in Machine Learning](https://getvm.io/tutorials/exploring-fairness-in-machine-learning-for-international-development)                                                 | Video Courses       | Discover the importance of fairness and bias considerations in applying machine learning, especially in international development. Build your capacity with this valuable course.                                                                                          |

|      37 | [Deep Multi-Task and Meta Learning](https://getvm.io/tutorials/deep-multi-task-and-meta-learning)                                                                                         | Video Courses       | In-depth understanding of state-of-the-art multi-task learning and meta-learning algorithms for few-shot learning, transfer learning, and lifelong learning.                                                                                                               |

|      38 | [MIT's Artificial Intelligence Course](https://getvm.io/tutorials/mits-artificial-intelligence)                                                                                           | Video Courses       | Comprehensive introduction to fundamental AI concepts, including knowledge representation, problem solving, and learning. Develop intelligent systems and explore the role of AI in understanding human intelligence.                                                      |

|      39 | [The Little Book of Deep Learning](https://getvm.io/tutorials/the-little-book-of-deep-learning)                                                                                           | Technical Tutorials | A concise and informative guide covering key topics in deep learning, machine learning, and neural networks. Explore foundations, model architectures, and practical applications.                                                                                         |

|      40 | [Reinforcement Learning: An Introduction](https://getvm.io/tutorials/reinforcement-learning-an-introduction)                                                                              | Technical Tutorials | Comprehensive book on reinforcement learning, providing in-depth understanding for students and researchers in the field of machine learning.                                                                                                                              |

|      41 | [Python Machine Learning Projects](https://getvm.io/tutorials/python-machine-learning-projects)                                                                                           | Technical Tutorials | Explore the application of Python in machine learning projects with this comprehensive guide, covering algorithms, tools, and real-world applications.                                                                                                                     |

|      42 | [Practitioners guide to MLOps](https://getvm.io/tutorials/practitioners-guide-to-mlops)                                                                                                   | Technical Tutorials | Comprehensive whitepaper on MLOps best practices and strategies for effective deployment and management of ML systems in organizations.                                                                                                                                    |

|      43 | [Machine Learning from Scratch](https://getvm.io/tutorials/machine-learning-from-scratch)                                                                                                 | Technical Tutorials | Dive into the principles and algorithms of machine learning with "Machine Learning From Scratch" - a comprehensive guide for beginners and experienced practitioners alike.                                                                                                |

|      44 | [Free and Open Machine Learning](https://getvm.io/tutorials/free-and-open-machine-learning)                                                                                               | Technical Tutorials | Discover the power of open-source machine learning with this comprehensive guide, covering key concepts, architecture, and FOSS tools for practical business applications.                                                                                                 |

|      45 | [Deep Learning for Coders with Fastai and PyTorch](https://getvm.io/tutorials/deep-learning-for-coders-with-fastai-and-pytorch)                                                           | Technical Tutorials | Comprehensive introduction to deep learning using the fastai library and PyTorch, suitable for beginners and experienced coders.                                                                                                                                           |

|      46 | [Approaching Almost Any Machine Learning Problem](https://getvm.io/tutorials/approaching-almost-any-machine-learning-problem)                                                             | Technical Tutorials | Comprehensive guide to problem-solving approaches in machine learning, suitable for beginners and experienced practitioners. Covers a wide range of ML topics and techniques.                                                                                              |

|      47 | [Algorithms for Reinforcement Learning](https://getvm.io/tutorials/algorithms-for-reinforcement-learning)                                                                                 | Technical Tutorials | Comprehensive guide to reinforcement learning algorithms, covering dynamic programming, temporal difference, Monte-Carlo methods, and more. Suitable for researchers, students, and practitioners in AI, ML, and control engineering.                                      |

|      48 | [A Selective Overview of Deep Learning](https://getvm.io/tutorials/a-selective-overview-of-deep-learning)                                                                                 | Technical Tutorials | Comprehensive overview of key concepts and recent advancements in deep learning, covering neural network models, training techniques, and theoretical foundations.                                                                                                         |

|      49 | [A First Encounter with Machine Learning](https://getvm.io/tutorials/a-first-encounter-with-machine-learning)                                                                             | Technical Tutorials | Explore fundamental machine learning concepts, algorithms, and applications in data science. Suitable for beginners interested in learning about this rapidly growing field.                                                                                               |

|      50 | [A Comprehensive Guide to Machine Learning](https://getvm.io/tutorials/a-comprehensive-guide-to-machine-learning)                                                                         | Technical Tutorials | Detailed resource on machine learning, data science, and artificial intelligence. Authored by experienced experts, suitable for beginners and experienced learners.                                                                                                        |

|      51 | [A Brief Introduction to Machine Learning for Engineers](https://getvm.io/tutorials/a-brief-introduction-to-machine-learning-for-engineers)                                               | Technical Tutorials | Gain a solid understanding of machine learning concepts and techniques for engineers. Covers supervised, unsupervised, probabilistic models, and advanced topics.                                                                                                          |

|      52 | [Data Mining Concepts and Techniques](https://getvm.io/tutorials/data-mining-concepts-and-techniques)                                                                                     | Technical Tutorials | Comprehensive coverage of data mining concepts and techniques, including data preprocessing, classification, clustering, and association rule mining. Essential resource for students, researchers, and professionals in data mining, machine learning, and data analysis. |

|      53 | [Machine Learning For Dummies, IBM Limited Edition](https://getvm.io/tutorials/machine-learning-for-dummies-ibm-limited-edition)                                                          | Technical Tutorials | Comprehensive guide to machine learning and data science, suitable for beginners and experienced professionals. Authored by experts Daniel Kirsch and Judith Hurwitz.                                                                                                      |

|      54 | [Getting Started with Artificial Intelligence , 2nd Edition](https://getvm.io/tutorials/getting-started-with-artificial-intelligence-2nd-edition)                                         | Technical Tutorials | Comprehensive introduction to AI, covering machine learning and data science. Practical guide to building enterprise applications with real-world examples.                                                                                                                |

|      55 | [Graduate Artificial Intelligence](https://getvm.io/tutorials/15-780-graduate-artificial-intelligence-spring-14-cmu)                                                                      | University Courses  | Comprehensive coverage of graduate-level artificial intelligence topics, including search, optimization, machine learning, and planning. Recommended for graduate students interested in a thorough introduction to AI.                                                    |

|      56 | [Artificial Intelligence](https://getvm.io/tutorials/artificial-intelligence-iit-kharagpur)                                                                                               | University Courses  | Comprehensive introduction to Artificial Intelligence (AI) fundamentals, techniques, and applications. Taught by experts from prestigious IIT Kharagpur.                                                                                                                   |

|      57 | [Artificial Intelligence](https://getvm.io/tutorials/artificial-intelligence-iit-madras)                                                                                                  | University Courses  | Comprehensive introduction to Artificial Intelligence from IIT Madras, covering machine learning, NLP, computer vision, and more. Ideal for students and professionals.                                                                                                    |

|      58 | [Artificial Intelligence](https://getvm.io/tutorials/6034-artificial-intelligence-mit-ocw)                                                                                                | University Courses  | Explore the core concepts of AI, including search, logic, reasoning, knowledge representation, and machine learning. Hands-on programming assignments and insights from experienced instructors.                                                                           |

|      59 | [Artificial Intelligence: Principles & Techniques](https://getvm.io/tutorials/cs221-artificial-intelligence-principles-and-techniques-autumn-2019-stanford-university)                    | University Courses  | Comprehensive introduction to AI principles and techniques, taught by experienced Stanford faculty. Hands-on projects and cutting-edge research opportunities.                                                                                                             |

|      60 | [Introduction to Artificial Intelligence](https://getvm.io/tutorials/cs322-introduction-to-artificial-intelligence-winter-2012-13-ubc)                                                    | University Courses  | Explore the fundamental concepts and techniques of artificial intelligence with this comprehensive course from renowned expert Professor Alan K. Mackworth at the University of British Columbia.                                                                          |

|      61 | [Intro to Artificial Intelligence](https://getvm.io/tutorials/mooc-intro-to-artificial-intelligence-udacity)                                                                              | University Courses  | Comprehensive coverage of key AI concepts and techniques, hands-on projects, and experienced instructors from Udacity. Ideal for students, professionals, and AI enthusiasts.                                                                                              |

|      62 | [Applications of Artificial Intelligence](https://getvm.io/tutorials/cse-592-applications-of-artificial-intelligence-winter-2003-university-of-washington)                                | University Courses  | Comprehensive coverage of fundamental AI concepts and techniques, including search, planning, Bayesian networks, machine learning, and more. Hands-on projects and presentations for practical application.                                                                |

|      63 | [Graduate Course in Artificial Intelligence](https://getvm.io/tutorials/graduate-course-in-artificial-intelligence-autumn-2012-university-of-washington)                                  | University Courses  | Comprehensive introduction to Artificial Intelligence (AI) covering search algorithms, knowledge representation, machine learning, and natural language processing. Hands-on experience with AI algorithms.                                                                |

|      64 | [Introduction to Artificial Intelligence](https://getvm.io/tutorials/cs-4804-introduction-to-artificial-intelligence-fall-2016)                                                           | University Courses  | Comprehensive AI course covering search, knowledge representation, reasoning, machine learning, and natural language processing. Hands-on projects and exposure to cutting-edge AI research.                                                                               |

|      65 | [Machine Learning for Computer Vision](https://getvm.io/tutorials/machine-learning-for-computer-vision-tu-munich)                                                                         | University Courses  | Comprehensive course on machine learning and its applications in computer vision, taught by experts from the renowned TUM computer vision research group.                                                                                                                  |

|      66 | [Machine Learning for Computer Vision](https://getvm.io/tutorials/machine-learning-for-computer-vision-winter-2017-2018-uniheidelberg)                                                    | University Courses  | Dive into the fundamentals of machine learning and its application to computer vision tasks like image classification, object detection, and segmentation. Taught by experienced researchers from the University of Heidelberg.                                            |

|      67 | [Advanced Computer Vision](https://getvm.io/tutorials/cap-6412-advanced-computer-vision-university-of-central-florida)                                                                    | University Courses  | Comprehensive review of recent advances in computer vision, preparing students for graduate research in this field. Hands-on programming projects and cutting-edge research discussions.                                                                                   |

|      68 | [Data Mining: Learning From Large Datasets](https://getvm.io/tutorials/data-mining-learning-from-large-datasets-fall-2017-eth-zurich)                                                     | University Courses  | Comprehensive data mining course covering supervised and unsupervised learning, feature engineering, and model evaluation. Hands-on experience with real-world datasets.                                                                                                   |

|      69 | [Statistical Aspects of Data Mining](https://getvm.io/tutorials/statistics-202-statistical-aspects-of-data-mining-summer-2007-google)                                                     | University Courses  | Comprehensive data mining course covering regression, classification, and clustering techniques. Hands-on exercises and real-world datasets. Taught by experienced Google instructors.                                                                                     |

|      70 | [Data Mining Course](https://getvm.io/tutorials/cs-51406140-data-mining-spring-2020-university-of-utah-by-prof-jeff-phillips)                                                             | University Courses  | Comprehensive data mining course covering statistical principles, similarity measures, clustering, classification, and real-world data analysis projects.                                                                                                                  |

|      71 | [Data Mining](https://getvm.io/tutorials/cs-51406140-data-mining-spring-2023-university-of-utah-by-prof-ana-marasovi)                                                                     | University Courses  | Explore key data mining topics like similarity search, clustering, regression, and graph analysis in this comprehensive course at the University of Utah.                                                                                                                  |

|      72 | [Data Mining Course](https://getvm.io/tutorials/csep-546-data-mining-pedro-domingos-sp-2016-university-of-washington)                                                                     | University Courses  | Comprehensive data mining course at the University of Washington, covering a wide range of techniques and algorithms, taught by an expert in the field.                                                                                                                    |

|      73 | [Deep Learning CMU](https://getvm.io/tutorials/deep-learning-cmu)                                                                                                                         | University Courses  | Explore the world of deep learning through expert-led video lectures from Carnegie Mellon University. Dive into neural networks, CNN, RNN, and more.                                                                                                                       |

|      74 | [Deep Learning Systems](https://getvm.io/tutorials/10-414714-deep-learning-systems-cmu)                                                                                                   | University Courses  | Comprehensive introduction to deep learning systems, covering machine learning, neural networks, optimization, and hardware acceleration. Hands-on implementation of key concepts.                                                                                         |

|      75 | [Intermediate Deep Learning](https://getvm.io/tutorials/cmu-10-417-10-617-intermediate-deep-learning-fall-2022-by-ruslan-salakhutdinov)                                                   | University Courses  | Comprehensive course on advanced deep learning techniques, taught by leading expert Ruslan Salakhutdinov. Hands-on experience with cutting-edge models and applications.                                                                                                   |

|      76 | [Neural Networks for Machine Learning](https://getvm.io/tutorials/mooc-neural-networks-for-machine-learning-geoffrey-hinton-2016-coursera)                                                | University Courses  | Comprehensive introduction to neural networks and machine learning from renowned expert Geoffrey Hinton. Covers fundamentals, advanced topics, and hands-on coding exercises.                                                                                              |

|      77 | [Deep Learning Course](https://getvm.io/tutorials/nyu-deep-learning-spring-2021)                                                                                                          | University Courses  | Comprehensive course on deep learning, covering fundamental concepts, neural network architectures, and hands-on implementation. Taught by experienced instructor from New York University.                                                                                |

|      78 | [Designing, Visualizing & Understanding Deep Neural Networks](https://getvm.io/tutorials/cs294-129-designing-visualizing-and-understanding-deep-neural-networks)                          | University Courses  | Explore the design principles, visualization tools, and theoretical understanding of deep neural networks in this comprehensive course. Ideal for students interested in AI, computer vision, and natural language processing.                                             |

|      79 | [Deep Learning](https://getvm.io/tutorials/deep-learning-stanford-university)                                                                                                             | University Courses  | Learn top machine learning techniques, including linear regression and supervised learning, with hands-on implementation experience. Taught by experienced instructors from Stanford University.                                                                           |

|      80 | [Full Stack DL Bootcamp 2019](https://getvm.io/tutorials/full-stack-dl-bootcamp-2019-uc-berkeley)                                                                                         | University Courses  | Comprehensive bootcamp covering the full stack of deep learning, from fundamentals to state-of-the-art models. Hands-on experience in building and deploying real-world deep learning applications.                                                                        |

|      81 | [Nvidia Machine Learning Class](https://getvm.io/tutorials/nvidia-machine-learning-class)                                                                                                 | University Courses  | Comprehensive Nvidia Machine Learning Class covering supervised, unsupervised learning, deep learning, and more. Presented by experienced experts with real-world examples.                                                                                                |

|      82 | [Statistical Learning in Practice](https://getvm.io/tutorials/cambridge-statistical-learning-in-practice-2021-by-alberto-j-coca)                                                          | University Courses  | Practical introduction to statistical learning techniques, covering linear regression to advanced methods like tree-based models and SVMs. Hands-on exercises and expert instruction.                                                                                      |

|      83 | [Reinforcement Learning Course](https://getvm.io/tutorials/reinforcement-learning-course-at-asu-spring-2022)                                                                              | University Courses  | Comprehensive Reinforcement Learning Course at Arizona State University (ASU) covering algorithms, deep RL, and real-world applications.                                                                                                                                   |

|      84 | [Statistical Machine Learning](https://getvm.io/tutorials/statistical-machine-learning-s2023-benyamin-ghojogh)                                                                            | University Courses  | Comprehensive course on statistical machine learning techniques like linear regression, logistic regression, decision trees, and more. Taught by an experienced instructor.                                                                                                |

|      85 | [Foundations of Machine Learning Boot Camp](https://getvm.io/tutorials/foundations-of-machine-learning-boot-camp-berkeley-simons-institute)                                               | University Courses  | Comprehensive online course providing a solid foundation in machine learning principles and techniques, developed by the renowned Berkeley Simons Institute.                                                                                                               |

|      86 | [Foundations of Machine Learning](https://getvm.io/tutorials/foundations-of-machine-learning-blmmoberg-edu)                                                                               | University Courses  | Comprehensive machine learning course covering a wide range of topics, designed to provide a deep understanding of fundamental concepts and techniques.                                                                                                                    |

|      87 | [Machine Learning & Data Mining](https://getvm.io/tutorials/cs155-machine-learning-data-mining-2017-caltech)                                                                              | University Courses  | Comprehensive coverage of fundamental machine learning and data mining techniques, taught by experienced Caltech instructors. Hands-on programming assignments and real-world applications.                                                                                |

|      88 | [CS 156](https://getvm.io/tutorials/cs-156-learning-from-data-caltech)                                                                                                                    | University Courses  | Comprehensive machine learning course from Caltech's Feynman Prize winner, covering core concepts and techniques in-depth.                                                                                                                                                 |

|      89 | [Foundations of Machine Learning](https://getvm.io/tutorials/cms-165-foundations-of-machine-learning-and-statistical-inference-2020-caltech)                                              | University Courses  | Comprehensive introduction to machine learning and statistical inference, taught by experienced Caltech faculty. Hands-on exercises and projects to reinforce key concepts.                                                                                                |

|      90 | [Introduction to Machine Learning & Pattern Recognition](https://getvm.io/tutorials/introduction-to-machine-learning-and-pattern-recognition-cbcsl-osu)                                   | University Courses  | Comprehensive course covering supervised/unsupervised learning, feature extraction, classification, regression, and clustering. Hands-on experience with real-world datasets and practical applications.                                                                   |

|      91 | [10-601 Machine Learning](https://getvm.io/tutorials/10-601-machine-learning-cmu-fall-2017)                                                                                               | University Courses  | Comprehensive introduction to machine learning, covering supervised, unsupervised, neural networks, and reinforcement learning. Taught at prestigious Carnegie Mellon University.                                                                                          |

|      92 | [Introduction to Machine Learning](https://getvm.io/tutorials/10-301601-introduction-to-machine-learning-spring-2020-cmu)                                                                 | University Courses  | Explore the fundamental concepts and algorithms of machine learning with experienced instructors from Carnegie Mellon University.                                                                                                                                          |

|      93 | [Introduction to Machine Learning](https://getvm.io/tutorials/10-301601-introduction-to-machine-learning-fall-2023-cmu)                                                                   | University Courses  | Comprehensive coverage of machine learning algorithms and techniques, hands-on experience, and exposure to cutting-edge research in this highly recommended course at Carnegie Mellon University.                                                                          |

|      94 | [Machine Learning with Large Datasets](https://getvm.io/tutorials/10-605-machine-learning-with-large-datasets-fall-2016-cmu)                                                              | University Courses  | Comprehensive course on scalable machine learning algorithms, distributed computing, and cloud-based tools for handling large datasets. Ideal for data-driven decision making and complex problem-solving.                                                                 |

|      95 | [Statistical Machine Learning](https://getvm.io/tutorials/10-70236-702-statistical-machine-learning-larry-wasserman-spring-2016-cmu)                                                      | University Courses  | Comprehensive course in statistical machine learning, including linear regression, classification, nonparametric methods, and more. Taught by renowned instructors Larry Wasserman and Ryan Tibshirani.                                                                    |

|      96 | [Advanced Introduction to Machine Learning](https://getvm.io/tutorials/10-715-advanced-introduction-to-machine-learning-cmu)                                                              | University Courses  | Comprehensive and in-depth exploration of fundamental machine learning concepts and techniques, including deep learning, clustering, kernel machines, and graphical models.                                                                                                |

|      97 | [Convex Optimization](https://getvm.io/tutorials/10-725-convex-optimization-spring-2015-cmu)                                                                                              | University Courses  | Explore the fundamentals of convex optimization, including convexity, optimization basics, and canonical problem forms. Recommended for students interested in machine learning and optimization.                                                                          |

|      98 | [Convex Optimization: Fundamentals, Algorithms & Applications](https://getvm.io/tutorials/10-725-convex-optimization-fall-2016-cmu)                                                       | University Courses  | Comprehensive introduction to convex optimization, covering theory, algorithms, and practical applications for graduate students in machine learning, statistics, and related fields.                                                                                      |

|      99 | [Optimization](https://getvm.io/tutorials/10-725-optimization-fall-2012-cmu)                                                                                                              | University Courses  | Comprehensive optimization course covering first-order methods, Newton's method, duality, and advanced topics. Taught by experienced instructors at Carnegie Mellon University.                                                                                            |

|     100 | [Advanced Optimization & Randomized Methods](https://getvm.io/tutorials/10-801-advanced-optimization-and-randomized-methods-cmu)                                                          | University Courses  | Explore powerful algorithmic tools for tackling large-scale data problems in machine learning and optimization. Gain a solid foundation for research in this cutting-edge field.                                                                                           |

|     101 | [Deep Reinforcement Learning & Control](https://getvm.io/tutorials/cmu-10-703-deep-reinforcement-learning-control-fall-2022-by-katerina-fragkiadaki)                                      | University Courses  | Explore the latest advancements in deep reinforcement learning with this comprehensive course by leading expert Katerina Fragkiadaki. Gain hands-on experience and tackle complex decision-making problems.                                                                |

|     102 | [Applied Machine Learning](https://getvm.io/tutorials/coms-w4995-applied-machine-learning-spring-2020-columbia-university)                                                                | University Courses  | Practical machine learning techniques, from data preprocessing to model deployment. Hands-on experience with popular libraries and real-world datasets.                                                                                                                    |

|     103 | [Learning with Big Messy Data](https://getvm.io/tutorials/orie-47415741-learning-with-big-messy-data-cornell)                                                                             | University Courses  | Explore a wide range of machine learning and data analysis topics, including exploratory data analysis, linear regression, and feature engineering, with hands-on experience on real-world datasets.                                                                       |

|     104 | [Machine Learning Hardware & Systems](https://getvm.io/tutorials/cornell-ece-5545-machine-learning-hardware-and-systems-spring-2022-by-mohamed-abdelfattah)                               | University Courses  | Explore the hardware and systems aspects of machine learning with this comprehensive course by Prof. Mohamed Abdelfattah. Gain insights into deep neural network computations, hardware accelerators, and real-world ML deployment.                                        |

|     105 | [Introduction to Reinforcement Learning](https://getvm.io/tutorials/cs-47895789-introduction-to-reinforcement-learning-cornell)                                                           | University Courses  | Explore the fundamental concepts and algorithms of reinforcement learning, a powerful machine learning approach for optimal decision-making, with hands-on programming assignments.                                                                                        |

|     106 | [Machine Learning](https://getvm.io/tutorials/cs47805780-machine-learning-fall-2013-cornell-university)                                                                                   | University Courses  | Comprehensive course covering a wide range of machine learning techniques, including classification, structured models, clustering, and recommender systems. Provides theoretical foundations and hands-on experimentation.                                                |

|     107 | [Machine Learning](https://getvm.io/tutorials/cs47805780-machine-learning-fall-2018-cornell-university)                                                                                   | University Courses  | Dive into the fundamentals of machine learning with this comprehensive course from Cornell University. Explore supervised, unsupervised, and model selection techniques.                                                                                                   |

|     108 | [Probabilistic Graphical Models](https://getvm.io/tutorials/mooc-probabilistic-graphical-models-coursera)                                                                                 | University Courses  | Learn the fundamental concepts and techniques of probabilistic graphical models, a powerful tool for representing and reasoning about uncertainty in complex systems.                                                                                                      |

|     109 | [Learning in Graphical Models](https://getvm.io/tutorials/uc-irvine-cs-274b-learning-in-graphical-models-spring-2021-by-erik-sudderth)                                                    | University Courses  | Comprehensive course on advanced topics in graphical models, including probabilistic inference, parameter learning, and structure learning. Taught by expert Erik Sudderth.                                                                                                |

|     110 | [Introduction to Machine Learning](https://getvm.io/tutorials/introduction-to-machine-learning-spring-2018-eth-zurich)                                                                    | University Courses  | Comprehensive machine learning course from leading experts at ETH Zurich. Covers fundamentals, algorithms, and real-world applications. Free online video lectures.                                                                                                        |

|     111 | [Stochastic Methods for Data Analysis, Inference & Optimization](https://getvm.io/tutorials/am-207-stochastic-methods-for-data-analysis-inference-and-optimization-harvard-university)    | University Courses  | Explore the powerful techniques of Monte Carlo methods and their applications in data analysis, inference, and optimization at Harvard University.                                                                                                                         |

|     112 | [Pattern Recognition](https://getvm.io/tutorials/pattern-recognition-iisc-bangalore)                                                                                                      | University Courses  | Comprehensive NPTEL course on pattern recognition techniques, featuring supervised and unsupervised learning, practical applications, and hands-on exercises.                                                                                                              |

|     113 | [Introduction to Machine Learning](https://getvm.io/tutorials/introduction-to-machine-learning-iit-kharagpur)                                                                             | University Courses  | Comprehensive coverage of machine learning fundamentals, hands-on experience with real-world datasets, and a verified certificate upon completion.                                                                                                                         |

|     114 | [Pattern Recognition and Application](https://getvm.io/tutorials/pattern-recognition-and-application-iit-kharagpur)                                                                       | University Courses  | Comprehensive course on pattern recognition techniques and applications, taught by experts from the prestigious IIT Kharagpur.                                                                                                                                             |

|     115 | [Introduction to Machine Learning](https://getvm.io/tutorials/introduction-to-machine-learning-iit-madras)                                                                                | University Courses  | Comprehensive machine learning course from IIT Madras, covering supervised, unsupervised learning, regression, classification, and more. Ideal for beginners and experienced learners.                                                                                     |

|     116 | [Pattern Recognition](https://getvm.io/tutorials/pattern-recognition-iit-madras)                                                                                                          | University Courses  | Comprehensive introduction to pattern recognition techniques including statistical, neural network, and support vector machine approaches. Hands-on experience with implementation.                                                                                        |

|     117 | [Algorithms for Big Data](https://getvm.io/tutorials/algorithms-for-big-data-iit-madras)                                                                                                  | University Courses  | Explore fundamental algorithmic techniques and data structures for processing large-scale datasets, including MapReduce, streaming algorithms, and sketching techniques.                                                                                                   |

|     118 | [Reinforcement Learning Course](https://getvm.io/tutorials/reinforcement-learning-iit-madras)                                                                                             | University Courses  | Comprehensive introduction to the core concepts, algorithms, and applications of reinforcement learning. Taught by experienced faculty from IIT Madras.                                                                                                                    |

|     119 | [Statistical Learning Theory](https://getvm.io/tutorials/eth-zurich-statistical-learning-theory-spring-2021-by-joachim-m-buhmann)                                                         | University Courses  | Comprehensive course on the fundamental principles and techniques of statistical learning theory, taught by renowned expert Joachim M. Buhmann at ETH Zurich.                                                                                                              |

|     120 | [EPFL CS 233](https://getvm.io/tutorials/epfl-cs-233-introduction-to-machine-learning-fall-2022-by-mathieu-salzmann)                                                                      | University Courses  | Comprehensive course on machine learning fundamentals, taught by expert Mathieu Salzmann at EPFL. Includes video lectures for accessible learning.                                                                                                                         |

|     121 | [Statistical Machine Learning](https://getvm.io/tutorials/sfu-cmpt-727-statistical-machine-learning-spring-2022-2023-by-maxwell-libbrecht)                                                | University Courses  | Gain a strong foundation in statistical machine learning with SFU CMPT 727, taught by expert Maxwell Libbrecht. Covers Bayesian methods, graphical models, and deep learning.                                                                                              |

|     122 | [Machine Learning](https://getvm.io/tutorials/6036-machine-learning-broderick-mit-fall-2020)                                                                                              | University Courses  | Comprehensive introduction to machine learning, covering supervised, unsupervised, neural networks, and deep learning. Taught by experienced MIT instructor.                                                                                                               |

|     123 | [Efficient Machine Learning](https://getvm.io/tutorials/mit-65940-efficientmlai-lecture-fall-2023)                                                                                        | University Courses  | Explore the latest advancements in efficient machine learning techniques at the MIT 6.5940 EfficientML.ai Lecture, Fall 2023. Learn from industry experts and gain insights into optimizing AI solutions.                                                                  |

|     124 | [MIT 6.036](https://getvm.io/tutorials/mit-6036-introduction-to-machine-learning-spring-2019-by-leslie-kaelbling)                                                                         | University Courses  | Comprehensive coverage of machine learning fundamentals, taught by renowned expert Professor Leslie Kaelbling. Hands-on programming assignments and accessible for students with computer science and mathematics background.                                              |

|     125 | [Algorithmic Aspects of Machine Learning](https://getvm.io/tutorials/18409-algorithmic-aspects-of-machine-learning-spring-2015-mit)                                                       | University Courses  | Explore advanced machine learning algorithms, including non-negative matrix factorization, tensor decompositions, and more in this MIT course.                                                                                                                             |

|     126 | [Statistical Learning Theory & Applications](https://getvm.io/tutorials/9520-statistical-learning-theory-and-applications-fall-2015-mit)                                                  | University Courses  | Explore the fundamental concepts and techniques of statistical learning theory, covering supervised and unsupervised learning, regression, classification, and more.                                                                                                       |

|     127 | [Introduction to Data-Centric AI](https://getvm.io/tutorials/introduction-to-data-centric-ai-mit)                                                                                         | University Courses  | Discover practical techniques to improve dataset quality and boost real-world machine learning performance with this first-ever Data-Centric AI course from MIT.                                                                                                           |

|     128 | [Computational Thinking & Data Science](https://getvm.io/tutorials/60002-introduction-to-computational-thinking-and-data-science-mit-ocw)                                                 | University Courses  | Explore fundamental computer science and data science concepts with Python programming for data analysis and problem-solving. Suitable for beginners and experienced learners.                                                                                             |

|     129 | [Undergraduate Machine Learning at UBC 2012](https://getvm.io/tutorials/undergraduate-machine-learning-at-ubc-2012-nando-de-freitas)                                                      | University Courses  | Comprehensive undergraduate-level machine learning course taught by renowned expert Nando de Freitas at the University of British Columbia in 2012. Covers fundamental concepts and techniques.                                                                            |

|     130 | [Machine Learning Course](https://getvm.io/tutorials/machine-learning-2013-nando-de-freitas-ubc)                                                                                          | University Courses  | Comprehensive machine learning course taught by renowned expert Nando de Freitas at the University of British Columbia (UBC). Covers supervised, unsupervised, deep, and reinforcement learning.                                                                           |

|     131 | [Probabilistic Graphical Models](https://getvm.io/tutorials/probabilistic-graphical-models-spring-2018-notre-dame)                                                                        | University Courses  | Comprehensive introduction to probabilistic graphical models, covering theory, algorithms, and real-world applications in machine learning, computer vision, and natural language processing.                                                                              |

|     132 | [Data Science for Dynamical Systems](https://getvm.io/tutorials/data-science-for-dynamical-systems-by-oliver-wallscheid-sebastian-peitz)                                                  | University Courses  | Explore data science techniques for analyzing and controlling dynamic systems with this comprehensive course. Covers system identification, model predictive control, and more.                                                                                            |

|     133 | [High Dimensional Analysis: Random Matrices and Machine Learning](https://getvm.io/tutorials/high-dimensional-analysis-random-matrices-and-machine-learning-by-roland-speicher)           | University Courses  | Explore the theoretical foundations and practical applications of high dimensional analysis, random matrices, and their role in machine learning with this comprehensive course by renowned expert Roland Speicher.                                                        |

|     134 | [Markov Chains & Algorithmic Applications](https://getvm.io/tutorials/epfl-com-516-markov-chains-and-algorithmic-applications-spring-2020-by-olivier-leveque)                             | University Courses  | Comprehensive course on Markov chains and their algorithmic applications, taught by Olivier Leveque at EPFL. Covers stationary distributions, ergodicity, and real-world problem-solving.                                                                                  |

|     135 | [Foundations of Reinforcement Learning](https://getvm.io/tutorials/ece524-foundations-of-reinforcement-learning-at-princeton-university-spring-2024)                                      | University Courses  | Comprehensive introduction to the fundamentals of reinforcement learning, including Markov decision processes, dynamic programming, and temporal-difference learning.                                                                                                      |

|     136 | [Intro to Machine Learning](https://getvm.io/tutorials/intro-to-machine-learning-and-statistical-pattern-classification-prof-sebastian-raschka)                                           | University Courses  | Comprehensive introduction to machine learning and statistical pattern classification, combining theoretical foundations with practical hands-on experience using Python.                                                                                                  |

|     137 | [Advanced Machine Learning](https://getvm.io/tutorials/advanced-machine-learning-2021-2022-sem-i-by-prof-madhavan-mukund-cmi)                                                             | University Courses  | Explore the latest advancements in machine learning, including deep learning, Gaussian process regression, Bayesian optimization, and more, taught by an experienced professor at the Chennai Mathematical Institute.                                                      |

|     138 | [PURDUE Machine Learning Summer School 2011](https://getvm.io/tutorials/purdue-machine-learning-summer-school-2011)                                                                       | University Courses  | Comprehensive course covering supervised, unsupervised, deep, and reinforcement learning, taught by experienced Purdue University instructors. Hands-on exercises and access to valuable resources.                                                                        |

|     139 | [Statistical Rethinking](https://getvm.io/tutorials/statistical-rethinking-winter-2015-richard-mcelreath)                                                                                 | University Courses  | Comprehensive introduction to Bayesian statistical modeling, covering probability theory, MCMC, and practical applications. Taught by renowned statistician Richard McElreath.                                                                                             |

|     140 | [Data Science](https://getvm.io/tutorials/cse519-data-science-fall-2016-skiena-sbu)                                                                                                       | University Courses  | Comprehensive data science course covering data collection, preprocessing, analysis, and visualization. Taught by renowned expert Steven Skiena at Stony Brook University.                                                                                                 |

|     141 | [Python and Machine Learning](https://getvm.io/tutorials/python-and-machine-learning-stanford-crowd-course-initiative)                                                                    | University Courses  | Comprehensive Python programming and machine learning course from Stanford Crowd Course Initiative. Gain practical experience in building and deploying ML models.                                                                                                         |

|     142 | [Statistical Learning with Python](https://getvm.io/tutorials/statistical-learning-with-python-stanford-online)                                                                           | University Courses  | Comprehensive introduction to statistical learning techniques, with hands-on Python implementations and emphasis on theory and practical applications.                                                                                                                     |

|     143 | [Statistical Learning](https://getvm.io/tutorials/mooc-statistical-learning-stanford-university)                                                                                          | University Courses  | In-depth 15-hour video course on machine learning techniques, taught by renowned Stanford professors. Gain theoretical and practical understanding of statistical learning.                                                                                                |

|     144 | [Machine Learning](https://getvm.io/tutorials/cs-229-machine-learning-stanford-university)                                                                                                | University Courses  | Comprehensive introduction to machine learning techniques, including supervised, unsupervised, and recent applications. Suitable for students with backgrounds in computer science, probability, and linear algebra.                                                       |

|     145 | [Stanford CS229M: Machine Learning Theory](https://getvm.io/tutorials/stanford-cs229m-machine-learning-theory-fall-2021)                                                                  | University Courses  | Dive deep into the theoretical foundations of machine learning with this comprehensive course from renowned experts at Stanford University.                                                                                                                                |

|     146 | [Introduction to Machine Learning](https://getvm.io/tutorials/ee104-introduction-to-machine-learning-stanford-university)                                                                 | University Courses  | Comprehensive course on machine learning fundamentals, including supervised, unsupervised, deep learning, and reinforcement learning. Taught by experts from Stanford.                                                                                                     |

|     147 | [Probabilistic Graphical Models](https://getvm.io/tutorials/probabilistic-graphical-models-daphne-koller-stanford-university)                                                             | University Courses  | Learn the principles and applications of probabilistic graphical models, widely used in machine learning and artificial intelligence.                                                                                                                                      |

|     148 | [Deep Multi-Task & Meta Learning](https://getvm.io/tutorials/cs-330-deep-multi-task-and-meta-learning-fall-2019-stanford-university)                                                      | University Courses  | Explore state-of-the-art multi-task learning and meta-learning algorithms in this graduate-level Stanford course, with a focus on coding problems and a course project.                                                                                                    |

|     149 | [Deep Multi-Task & Meta Learning I](https://getvm.io/tutorials/stanford-cs330-deep-multi-task-and-meta-learning-i-autumn-2022)                                                            | University Courses  | Explore state-of-the-art multi-task learning and meta-learning algorithms in this graduate-level course, preparing you for research in deep learning.                                                                                                                      |

|     150 | [Convex Optimization I](https://getvm.io/tutorials/ee364a-convex-optimization-i-stanford-university)                                                                                      | University Courses  | Comprehensive introduction to convex optimization theory and algorithms, taught by renowned expert Professor Stephen Boyd. Practical applications in engineering, economics, and more.                                                                                     |

|     151 | [CS224W: Machine Learning with Graphs](https://getvm.io/tutorials/cs224w-machine-learning-with-graphs-spring-2021-stanford-university)                                                    | University Courses  | Explore state-of-the-art graph machine learning techniques, including graph neural networks, graph embedding, and graph algorithms, with hands-on experience on real-world datasets.                                                                                       |

|     152 | [Reinforcement Learning](https://getvm.io/tutorials/cs234-reinforcement-learning-winter-2019-stanford-university)                                                                         | University Courses  | Comprehensive introduction to reinforcement learning, covering Markov Decision Processes, dynamic programming, and more. Taught by experts at Stanford University.                                                                                                         |

|     153 | [Introduction to Machine Learning](https://getvm.io/tutorials/cse474574-introduction-to-machine-learning-suny-university-at-buffalo)                                                      | University Courses  | Comprehensive coverage of machine learning algorithms and techniques. Hands-on projects and experienced faculty. Ideal for students interested in data science and AI.                                                                                                     |

|     154 | [Scalable Machine Learning](https://getvm.io/tutorials/cs-281b-scalable-machine-learning-alex-smola-uc-berkeley)                                                                          | University Courses  | Comprehensive course on scalable machine learning techniques for large-scale data analysis and internet applications, covering systems, statistics, algorithms, and more.                                                                                                  |

|     155 | [Machine Learning](https://getvm.io/tutorials/uc-berkeley-cs-189-289a-introduction-to-machine-learning-fall-2023-by-jennifer-listgarten-jitendra-malik)                                   | University Courses  | Comprehensive machine learning course from renowned professors at UC Berkeley, covering fundamental algorithms, deep learning models, and real-world applications.                                                                                                         |

|     156 | [Data Science Foundations](https://getvm.io/tutorials/data-8-the-foundations-of-data-science-uc-berkeley)                                                                                 | University Courses  | Explore the foundations of data science with the UC Berkeley Data 8 course, combining inferential thinking, computational thinking, and real-world relevance.                                                                                                              |

|     157 | [Data Science](https://getvm.io/tutorials/data-100-summer-19-uc-berkeley)                                                                                                                 | University Courses  | Comprehensive video series covering data preprocessing, exploratory analysis, statistical modeling, and machine learning from experienced UC Berkeley instructors.                                                                                                         |

|     158 | [Data Computing Concepts](https://getvm.io/tutorials/statistics-133-concepts-in-computing-with-data-fall-2013-uc-berkeley)                                                                | University Courses  | Explore data analysis, visualization, and programming with R in this comprehensive course from UC Berkeley. Suitable for beginners, learn essential data skills.                                                                                                           |

|     159 | [Analyzing Big Data with Twitter](https://getvm.io/tutorials/info-290-analyzing-big-data-with-twitter-uc-berkeley-school-of-information)                                                  | University Courses  | Gain hands-on experience in leveraging Twitter data to uncover insights and trends. Explore data analysis techniques, collaborate on real-world projects, and develop valuable data science skills.                                                                        |

|     160 | [Deep Reinforcement Learning](https://getvm.io/tutorials/cs-285-deep-reinforcement-learning-uc-berkeley)                                                                                  | University Courses  | Dive into the latest advancements in deep reinforcement learning with hands-on experience and expert guidance from UC Berkeley's CS 285 course.                                                                                                                            |

|     161 | [Machine Learning](https://getvm.io/tutorials/cs189-machine-learning-2022-ucb)                                                                                                            | University Courses  | Comprehensive introduction to machine learning, covering linear classifiers, gradient descent, and support vector machines. Taught by experts from UC Berkeley.                                                                                                            |

|     162 | [Introduction to Machine Learning](https://getvm.io/tutorials/cs-189289a-introduction-to-machine-learning-prof-jonathan-shewchuk-ucberkeley)                                              | University Courses  | Learn a wide range of machine learning algorithms, including perceptrons, SVMs, and neural networks, from renowned expert Prof. Jonathan Shewchuk.                                                                                                                         |

|     163 | [Reinforcement Learning](https://getvm.io/tutorials/reinforcement-learning-ucl)                                                                                                           | University Courses  | Comprehensive introduction to reinforcement learning concepts, algorithms, and applications. Learn from experts at University College London.                                                                                                                              |

|     164 | [Introduction to Reinforcement Learning](https://getvm.io/tutorials/introduction-to-reinforcement-learning-ucl)                                                                           | University Courses  | Explore the fundamentals of reinforcement learning, including Markov decision processes, value functions, and policy optimization. Hands-on exercises using OpenAI Gym.                                                                                                    |

|     165 | [Advanced Deep Learning](https://getvm.io/tutorials/advanced-deep-learning-reinforcement-learning-ucl)                                                                                    | University Courses  | Expand your knowledge of deep learning and reinforcement learning with this comprehensive course taught by renowned experts from University College London.                                                                                                                |

|     166 | [Reinforcement Learning](https://getvm.io/tutorials/ucl-course-2015-on-reinforcement-learning-by-david-silver-from-deepmind)                                                              | University Courses  | Comprehensive introduction to reinforcement learning, covering Markov decision processes, dynamic programming, and more. Taught by leading expert David Silver from DeepMind.                                                                                              |

|     167 | [Pattern Recognition & Machine Learning](https://getvm.io/tutorials/ucla-stat-c161-introduction-to-pattern-recognition-and-machine-learning-winter-2023-by-arash-amini)                   | University Courses  | Comprehensive course on pattern recognition and machine learning techniques, covering fundamentals, algorithms, and real-world applications. Ideal for data science and AI enthusiasts.                                                                                    |

|     168 | [Information Geometry & Applications](https://getvm.io/tutorials/ucsd-math-273b-information-geometry-and-its-applications-winter-2022-by-melvin-leok)                                     | University Courses  | Explore the mathematical foundations of information theory, machine learning, and optimization with UCSD's MATH 273B course on Information Geometry and its Applications.                                                                                                  |

|     169 | [Machine Learning Part 1a](https://getvm.io/tutorials/mooc-machine-learning-part-1a-udacitygeorgia-tech)                                                                                  | University Courses  | Gain a solid foundation in machine learning with this comprehensive Udacity/Georgia Tech course covering supervised learning, regression, and classification algorithms.                                                                                                   |

|     170 | [Machine Learning Course](https://getvm.io/tutorials/cs-446-machine-learning-fall-2016-uiuc)                                                                                              | University Courses  | Comprehensive introduction to machine learning algorithms and techniques, taught by experienced instructors from the University of Illinois at Urbana-Champaign.                                                                                                           |

|     171 | [Information Theory, Pattern Recognition & Neural Networks](https://getvm.io/tutorials/information-theory-pattern-recognition-and-neural-networks-university-of-cambridge)                | University Courses  | Comprehensive introduction to information theory, pattern recognition, and neural networks. Taught by experts from the University of Cambridge with practical applications and real-world examples.                                                                        |

|     172 | [Probabilistic Models](https://getvm.io/tutorials/probabilistic-models-university-of-helsinki)                                                                                            | University Courses  | Explore the fundamentals of probabilistic models and their applications in various fields. Offered by the University of Helsinki.                                                                                                                                          |

|     173 | [Large Scale Machine Learning](https://getvm.io/tutorials/sta-4273h-large-scale-machine-learning-winter-2015-university-of-toronto)                                                       | University Courses  | Comprehensive graduate-level course covering advanced machine learning techniques, including Bayesian methods, graphical models, and sequential data modeling. Hands-on experience with real-world datasets and programming assignments.                                   |

|     174 | [Statistical Inference in Big Data](https://getvm.io/tutorials/statistical-inference-in-big-data-university-of-toronto)                                                                   | University Courses  | Comprehensive coverage of statistical inference techniques for big data analysis, lectures by renowned experts, and hands-on demonstrations for practical learning.                                                                                                        |

|     175 | [Machine Learning](https://getvm.io/tutorials/cs-53506350-machine-learning-spring-2024-university-of-utah)                                                                                | University Courses  | Comprehensive course covering supervised and unsupervised learning, decision trees, online learning, and more. Develop a strong foundation in machine learning and its applications.                                                                                       |

|     176 | [Probabilistic Modeling](https://getvm.io/tutorials/cs-6190-probabilistic-modeling-spring-2016-university-of-utah)                                                                        | University Courses  | Comprehensive course on probabilistic modeling techniques, including Bayesian networks and Markov models, for data analysis and decision-making. Taught by experienced faculty at the University of Utah.                                                                  |

|     177 | [Clustering](https://getvm.io/tutorials/cs-6955-clustering-spring-2015-university-of-utah)                                                                                                | University Courses  | Learn the fundamental concepts and techniques of clustering, a key data mining and machine learning method for grouping similar objects. Hands-on exercises and real-world projects included.                                                                              |

|     178 | [Machine Learning](https://getvm.io/tutorials/machine-learning-pedro-domingos-university-of-washington)                                                                                   | University Courses  | Comprehensive introduction to machine learning techniques and algorithms, taught by Professor Pedro Domingos. Hands-on exercises, real-world case studies, and practical applications.                                                                                     |

|     179 | [Machine Learning](https://getvm.io/tutorials/cs-485685-machine-learning-shai-ben-david-university-of-waterloo)                                                                           | University Courses  | Comprehensive understanding of machine learning principles and techniques, taught by a renowned expert at the University of Waterloo.                                                                                                                                      |

|     180 | [Classification](https://getvm.io/tutorials/stat-441841-classification-winter-2017-waterloo)                                                                                              | University Courses  | Comprehensive course on classification techniques, including logistic regression, decision trees, and support vector machines. Ideal for students interested in machine learning and data science.                                                                         |

|     181 | [Reinforcement Learning](https://getvm.io/tutorials/cs885-reinforcement-learning-spring-2018-university-of-waterloo)                                                                      | University Courses  | Comprehensive course on reinforcement learning for AI, machine learning, and sequential decision-making problems. Covers core principles, algorithms, and real-world applications.                                                                                         |

|     182 | [Machine Learning Algorithms](https://getvm.io/tutorials/ut-austin-machine-learning-algorithms-statistical-learning-by-adam-klivans-qiang-liu)                                            | University Courses  | Comprehensive course on fundamental machine learning algorithms and statistical learning techniques, taught by renowned professors from the University of Texas at Austin.                                                                                                 |

|     183 | [Bandits and Online Learning](https://getvm.io/tutorials/ut-austin-ece-381v-bandits-and-online-learning-fall-2021-by-sanjay-shakkottai)                                                   | University Courses  | Comprehensive course on multi-armed bandits and online learning, taught by expert Sanjay Shakkottai. Gain hands-on experience with implementing and analyzing cutting-edge algorithms.                                                                                     |

|     184 | [Introduction to Machine Learning](https://getvm.io/tutorials/ece-5984-introduction-to-machine-learning-spring-2015-virginia-tech)                                                        | University Courses  | Comprehensive course on machine learning fundamentals, including supervised learning, probability, statistical estimation, and linear models. Hands-on exercises and real-world applications.                                                                              |

|     185 | [Machine Learning](https://getvm.io/tutorials/csx824ecex242-machine-learning-bert-huang-fall-2015-virginia-tech)                                                                          | University Courses  | Comprehensive coverage of machine learning algorithms and techniques, hands-on experience with real-world datasets and projects, taught by an expert in the field, Bert Huang.                                                                                             |

|     186 | [Introduction to Machine Learning for Coders](https://getvm.io/tutorials/introduction-to-machine-learning-for-coders)                                                                     | University Courses  | Comprehensive and practical learning experience in deep learning, empowering learners to start training models within minutes and apply deep learning to real-world problems.                                                                                              |

|     187 | [Mediterranean Machine Learning Summer School 2023](https://getvm.io/tutorials/mediterranean-machine-learning-summer-school-2023)                                                         | University Courses  | Comprehensive machine learning program with hands-on workshops, expert instruction, and networking opportunities in a scenic Mediterranean location.                                                                                                                       |

|     188 | [Microsoft Research](https://getvm.io/tutorials/microsoft-research-machine-learning-course)                                                                                               | University Courses  | Explore the comprehensive Microsoft Research machine learning course, covering supervised, unsupervised, deep, and reinforcement learning techniques. Presented by leading experts.                                                                                        |

|     189 | [Introduction to Machine Learning](https://getvm.io/tutorials/cs273a-introduction-to-machine-learning)                                                                                    | University Courses  | Explore the fundamental concepts of machine learning and data mining. Prepare for research or industry applications with a broad range of models and algorithms.                                                                                                           |

|     190 | [Machine Learning Crash Course 2015](https://getvm.io/tutorials/machine-learning-crash-course-2015)                                                                                       | University Courses  | Comprehensive machine learning course from MIT experts, covering fundamentals, supervised/unsupervised learning, model selection, and more. Suitable for beginners and experienced learners.                                                                               |

|     191 | [Machine Learning and Adaptive Intelligence](https://getvm.io/tutorials/com4509com6509-machine-learning-and-adaptive-intelligence-2015-16)                                                | University Courses  | Gain a strong foundation in machine learning and artificial intelligence with this comprehensive course covering probability theory, supervised and unsupervised learning, and more.                                                                                       |

|     192 | [Advanced Introduction to Machine Learning](https://getvm.io/tutorials/10715-advanced-introduction-to-machine-learning)                                                                   | University Courses  | Comprehensive coverage of advanced machine learning concepts and algorithms, hands-on experience with real-world projects, and exposure to the latest advancements in deep learning and reinforcement learning.                                                            |

|     193 | [Machine Learning for Engineers 2022](https://getvm.io/tutorials/machine-learning-for-engineers-2022)                                                                                     | University Courses  | Gain practical experience in applying machine learning techniques to solve real-world engineering problems with this comprehensive course covering theory, applications, and hands-on projects.                                                                            |

|     194 | [Introduction to Pattern Recognition & Machine Learning](https://getvm.io/tutorials/stats-c161c261-introduction-to-pattern-recognition-and-machine-learning-winter-2024)                  | University Courses  | Comprehensive course covering fundamental machine learning concepts, algorithms, and real-world applications. Hands-on experience with Python and popular libraries.                                                                                                       |

|     195 | [Regularization Methods for Machine Learning 2016](https://getvm.io/tutorials/regularization-methods-for-machine-learning-2016)                                                           | University Courses  | Comprehensive understanding of regularization methods, crucial for high-dimensional learning problems. Suitable for those interested in the latest developments in machine learning and its practical applications.                                                        |

|     196 | [ACP Summer School 2023](https://getvm.io/tutorials/acp-summer-school-2023-on-machine-learning-for-constraint-programming)                                                                | University Courses  | Comprehensive program exploring the intersection of machine learning and constraint programming. Hands-on workshops, networking, and exposure to cutting-edge research.                                                                                                    |

|     197 | [Reinforcement Learning](https://getvm.io/tutorials/cs-294-112-reinforcement-learning)                                                                                                    | University Courses  | Comprehensive introduction to reinforcement learning, covering fundamental concepts, cutting-edge algorithms, and real-world applications in robotics, game AI, and decision-making.                                                                                       |

|     198 | [Deep Reinforcement Learning](https://getvm.io/tutorials/nus-cs-6101-deep-reinforcement-learning)                                                                                         | University Courses  | Explore the fundamentals of deep reinforcement learning, including algorithms, frameworks, and practical applications in areas like game playing, robotics, and resource management.                                                                                       |

|     199 | [Reinforcement Learning](https://getvm.io/tutorials/ece-8851-reinforcement-learning)                                                                                                      | University Courses  | Comprehensive course on reinforcement learning, covering fundamental concepts, advanced algorithms, and real-world applications in AI, robotics, and more.                                                                                                                 |

|     200 | [Deep Reinforcement Learning](https://getvm.io/tutorials/cs294-112-deep-reinforcement-learning-sp17)                                                                                      | University Courses  | Comprehensive course on deep reinforcement learning, taught by a leading expert. Hands-on assignments and projects to apply the concepts.                                                                                                                                  |

|     201 | [Deep Reinforcement Learning Bootcamp](https://getvm.io/tutorials/deep-rl-bootcamp-berkeley-aug-2017)                                                                                     | University Courses  | Comprehensive deep RL course led by renowned experts from Berkeley, covering Markov Decision Processes, DQN, policy gradients, and more. Hands-on demos and code examples.                                                                                                 |

|     202 | [CMU Advanced NLP 2021](https://getvm.io/tutorials/cmu-advanced-nlp-2021)                                                                                                                 | University Courses  | Dive into advanced NLP topics like language models, dialogue systems, and multimodal learning. Taught by renowned experts, this course provides in-depth insights into the latest advancements in natural language processing.                                             |

|     203 | [Multilingual NLP](https://getvm.io/tutorials/cmu-cs11-737-multilingual-natural-language-processing)                                                                                      | University Courses  | Explore the latest advancements in multilingual natural language processing, including machine translation, cross-lingual information retrieval, and text generation.                                                                                                      |

|     204 | [Natural Language Processing](https://getvm.io/tutorials/natural-language-processing-michael-collins-columbia-university)                                                                 | University Courses  | Comprehensive NLP course from renowned expert Michael Collins at Columbia University. Covers language models, text classification, sequence labeling, and more.                                                                                                            |

|     205 | [Natural Language Processing](https://getvm.io/tutorials/mooc-natural-language-processing-coursera-university-of-michigan)                                                                | University Courses  | Comprehensive NLP course from University of Michigan covers language models, text classification, sequence-to-sequence learning, and more. Hands-on projects and assignments.                                                                                              |

|     206 | [Natural Language Processing](https://getvm.io/tutorials/natural-language-processing-iit-bombay)                                                                                          | University Courses  | Comprehensive NLP course from IIT Bombay covering language models, text preprocessing, POS tagging, sentiment analysis, and more. Hands-on exercises and industry-relevant skills.                                                                                         |

|     207 | [Natural Language Understanding](https://getvm.io/tutorials/stanford-xcs224u-natural-language-understanding-i-spring-2023)                                                                | University Courses  | Explore the latest techniques in natural language processing, including language models, text generation, and question answering. Taught by experts in the field.                                                                                                          |

|     208 | [Natural Language Understanding](https://getvm.io/tutorials/cs224u-natural-language-understanding-spring-2019-stanford-university)                                                        | University Courses  | Explore the latest advancements in natural language processing with this comprehensive course from Stanford University, taught by leading experts in the field.                                                                                                            |

|     209 | [Natural Language Processing](https://getvm.io/tutorials/cs-63405340-natural-language-processing-university-of-utah-spring-2024)                                                          | University Courses  | Comprehensive NLP course covering fundamentals, techniques, and real-world applications. Hands-on experience, expert instruction, and collaborative learning environment.                                                                                                  |

|     210 | [Recent Advances on Foundation Models](https://getvm.io/tutorials/cs-886-recent-advances-on-foundation-models-winter-2024-university-of-waterloo)                                         | University Courses  | Explore the latest developments in foundation models, a powerful machine learning technology, through this graduate-level course at the University of Waterloo.                                                                                                            |

|     211 | [Advanced Robotics](https://getvm.io/tutorials/cs287-advanced-robotics-at-uc-berkeley-fall-2019-instructor-pieter-abbeel)                                                                 | University Courses  | Explore cutting-edge robotics techniques and applications in this in-depth course taught by renowned expert Pieter Abbeel at UC Berkeley.                                                                                                                                  |

|     212 | [Speech Processing](https://getvm.io/tutorials/cmu-11-492-speech-processing-fall-2021-by-alan-w-black)                                                                                    | University Courses  | Comprehensive introduction to speech processing, including speech production, recognition, and synthesis. Taught by renowned expert Alan W. Black. Hands-on projects for practical experience.                                                                             |



## More



- [Free JavaScript Resources](https://github.com/getvmio/free-javascript-resources)

- [Free HTML Resources](https://github.com/getvmio/free-html-resources)

- [Free R Resources](https://github.com/getvmio/free-r-resources)

- [Free Java Resources](https://github.com/getvmio/free-java-resources)

- [Free Neural Networks Resources](https://github.com/getvmio/free-neural-networks-resources)

- [Free Natural Language Processing Resources](https://github.com/getvmio/free-natural-language-processing-resources)

- [Free Computer Science Resources](https://github.com/getvmio/free-computer-science-resources)

- [Free React Resources](https://github.com/getvmio/free-react-resources)

- [Free Security Resources](https://github.com/getvmio/free-security-resources)

- [Free Node.js Resources](https://github.com/getvmio/free-node-js-resources)

- [Free PyTorch Resources](https://github.com/getvmio/free-pytorch-resources)

- [Free Computer Architecture Resources](https://github.com/getvmio/free-computer-architecture-resources)

- [Free Functional Programming Resources](https://github.com/getvmio/free-functional-programming-resources)

- [Free Operating System Resources](https://github.com/getvmio/free-operating-system-resources)

- [Free Cryptography Resources](https://github.com/getvmio/free-cryptography-resources)

- [Free Compiler Resources](https://github.com/getvmio/free-compiler-resources)

- [Free Blockchain Resources](https://github.com/getvmio/free-blockchain-resources)

- [Free SQL Resources](https://github.com/getvmio/free-sql-resources)

- [Free Python Resources](https://github.com/getvmio/free-python-resources)

- [Free Unix Resources](https://github.com/getvmio/free-unix-resources)

- [Free Programming Resources](https://github.com/getvmio/free-programming-resources)

- [Free Object-Oriented Programming Resources](https://github.com/getvmio/free-object-oriented-programming-resources)

- [Free CSS Resources](https://github.com/getvmio/free-css-resources)

- [Free Web Development Resources](https://github.com/getvmio/free-web-development-resources)

- [Free Shell Scripting Resources](https://github.com/getvmio/free-shell-scripting-resources)

- [Free Rust Resources](https://github.com/getvmio/free-rust-resources)

- [Free Haskell Resources](https://github.com/getvmio/free-haskell-resources)

- [Free Software Development Resources](https://github.com/getvmio/free-software-development-resources)

- [Free Data Science Resources](https://github.com/getvmio/free-data-science-resources)

- [Free Git Resources](https://github.com/getvmio/free-git-resources)

- [Free Networking Resources](https://github.com/getvmio/free-networking-resources)

- [Free Game Development Resources](https://github.com/getvmio/free-game-development-resources)

- [Free TensorFlow Resources](https://github.com/getvmio/free-tensorflow-resources)

- [Free Distributed Systems Resources](https://github.com/getvmio/free-distributed-systems-resources)

- [Free Embedded Systems Resources](https://github.com/getvmio/free-embedded-systems-resources)

- [Free DevOps Resources](https://github.com/getvmio/free-devops-resources)

- [Free Docker Resources](https://github.com/getvmio/free-docker-resources)

- [Free Robotics Resources](https://github.com/getvmio/free-robotics-resources)

- [Free Computer Vision Resources](https://github.com/getvmio/free-computer-vision-resources)

- [Free Deep Learning Resources](https://github.com/getvmio/free-deep-learning-resources)

- [Free Cloud Computing Resources](https://github.com/getvmio/free-cloud-computing-resources)

- [Free Go Resources](https://github.com/getvmio/free-go-resources)

- [Free Data Structures Resources](https://github.com/getvmio/free-data-structures-resources)

- [Free Control Systems Resources](https://github.com/getvmio/free-control-systems-resources)

- [Free Artificial Intelligence Resources](https://github.com/getvmio/free-artificial-intelligence-resources)

- [Free Data Analysis Resources](https://github.com/getvmio/free-data-analysis-resources)

- [Free Ruby Resources](https://github.com/getvmio/free-ruby-resources)

- [Free C++ Resources](https://github.com/getvmio/free-cpp-resources)

- [Free Bash Resources](https://github.com/getvmio/free-bash-resources)

- [Free Cybersecurity Resources](https://github.com/getvmio/free-cybersecurity-resources)

- [Free Algorithm Resources](https://github.com/getvmio/free-algorithm-resources)

- [Free Database Resources](https://github.com/getvmio/free-database-resources)

- [Free C Resources](https://github.com/getvmio/free-c-resources)

- [Free Version Control Resources](https://github.com/getvmio/free-version-control-resources)

- [Free Linux Resources](https://github.com/getvmio/free-linux-resources)

- [Free Computer Graphics Resources](https://github.com/getvmio/free-computer-graphics-resources)