{"id":15076142,"url":"https://github.com/getvmio/free-tensorflow-resources","last_synced_at":"2025-02-26T17:41:39.889Z","repository":{"id":251137376,"uuid":"822447245","full_name":"getvmio/free-tensorflow-resources","owner":"getvmio","description":"TensorFlow Free Resources | This repo collects 24 of free resources for TensorFlow. ⚡ Harness the power of machine learning with our TensorFlow Dojo repository! 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Featuring a comprehensive set of free TensorFlow learning materials and a hands-on online environment, this is your training ground for building and deploying cutting-edge AI applications.\n\n## Resources\n\n|   Index | Name                                                                                                                                                                                        | Category            | Description                                                                                                                                                                                            |\n|---------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n|       1 | [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.                                          |\n|       2 | [Building a simple Generative Adversarial Network (GAN) using Tensorflow](https://getvm.io/tutorials/building-a-simple-generative-adversarial-network-gan-using-tensorflow)                 | Technical Tutorials | Hands-on introduction to building a simple Generative Adversarial Network (GAN) using TensorFlow. Understand the core concept, implement the model, and visualize the process.                         |\n|       3 | [Introduction to TensorFlow for AI, Machine Learning \u0026 Deep Learning](https://getvm.io/tutorials/introduction-to-tensorflow-for-artificial-intelligence-machine-learning-and-deep-learning) | Video Courses       | Gain hands-on experience in building neural networks, training them for computer vision, and understanding the use of convolutions to improve model performance.                                       |\n|       4 | [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.                             |\n|       5 | [Deep Learning Applications](https://getvm.io/tutorials/t81-558-applications-of-deep-neural-networks-by-jeff-heaton-2022-washington-university-in-st-louis)                                 | University Courses  | Explore the latest advancements in deep learning and its practical applications in computer vision, time series, security, NLP, and data generation.                                                   |\n|       6 | [Introduction to Artificial Intelligence](https://getvm.io/tutorials/cs-5804-introduction-to-artificial-intelligence-spring-2015)                                                           | University Courses  | Comprehensive AI course covering search, knowledge representation, reasoning, machine learning, and natural language processing. Hands-on experience with cutting-edge AI algorithms and applications. |\n|       7 | [Artificial Intelligence](https://getvm.io/tutorials/artificial-intelligence-hochschule-ravensburg-weingarten)                                                                              | University Courses  | Comprehensive overview of AI principles, hands-on experience with algorithms, and insights into the ethical implications of Artificial Intelligence.                                                   |\n|       8 | [Deep Learning for Computer Vision](https://getvm.io/tutorials/deep-learning-for-computer-vision-university-of-michigan)                                                                    | University Courses  | Comprehensive introduction to deep learning techniques for computer vision tasks, including image classification, object detection, and segmentation.                                                  |\n|       9 | [Neural Networks: Zero to Hero](https://getvm.io/tutorials/neural-networks-zero-to-hero-andrej-karpathy)                                                                                    | University Courses  | Comprehensive video series by renowned expert Andrej Karpathy, covering neural network fundamentals, advanced techniques, and practical applications.                                                  |\n|      10 | [Neural Networks and Applications](https://getvm.io/tutorials/neural-networks-and-applications-iit-kharagpur)                                                                               | University Courses  | Comprehensive introduction to neural networks, covering architectures, algorithms, and real-world applications in image recognition, NLP, and predictive modeling.                                     |\n|      11 | [Deep Learning](https://getvm.io/tutorials/cs7015-deep-learning-prof-mitesh-m-khapra-iit-madras)                                                                                            | University Courses  | Comprehensive overview of deep learning, covering fundamental concepts, architectures, and applications. Taught by Prof. Mitesh M. Khapra from IIT Madras.                                             |\n|      12 | [Introduction to Deep Learning](https://getvm.io/tutorials/6s191-introduction-to-deep-learning-mit)                                                                                         | University Courses  | Dive into the fundamentals of deep learning with MIT's intensive bootcamp, covering cutting-edge topics in computer vision, natural language processing, and more.                                     |\n|      13 | [Intro to Deep Learning \u0026 Generative Models](https://getvm.io/tutorials/intro-to-deep-learning-and-generative-models-course-prof-sebastian-raschka)                                         | University Courses  | Comprehensive course on deep learning fundamentals, generative models like VAEs and GANs, with hands-on tutorials using TensorFlow and PyTorch.                                                        |\n|      14 | [Deep Learning](https://getvm.io/tutorials/stat-157-deep-learning-2019-uc-berkeley)                                                                                                         | University Courses  | Comprehensive deep learning course from UC Berkeley covering neural networks, optimization, and real-world applications. Hands-on coding and experienced instructors.                                  |\n|      15 | [Deep Learning](https://getvm.io/tutorials/stat-946-deep-learning-university-of-waterloo)                                                                                                   | University Courses  | Comprehensive introduction to deep learning, covering fundamental concepts, advanced topics, and hands-on exercises using popular frameworks like TensorFlow and PyTorch.                              |\n|      16 | [Deep Learning for Computer Vision](https://getvm.io/tutorials/dlcv-deep-learning-for-computer-vision-upc-barcelona)                                                                        | University Courses  | Comprehensive course on deep learning for computer vision, covering CNN, RNN, GAN, and state-of-the-art models for image and video analysis.                                                           |\n|      17 | [Deep Learning: CS 182](https://getvm.io/tutorials/deep-learning-cs-182-spring-2021)                                                                                                        | University Courses  | Dive into the fundamentals of deep learning with this in-depth course, covering neural networks, optimization, and real-world applications in computer vision, NLP, and more.                          |\n|      18 | [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.          |\n|      19 | [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.                                  |\n|      20 | [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.                     |\n|      21 | [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.                          |\n|      22 | [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.                   |\n|      23 | [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.                                             |\n|      24 | [Natural Language Processing](https://getvm.io/tutorials/cs388-natural-language-processing-ut-austin)                                                                                       | University Courses  | Comprehensive online NLP course covering sentiment analysis, neural networks, word embeddings, and transformer language modeling. Includes hands-on coding assignments.                                |\n\n## More\n\n- [Free JavaScript Resources](https://github.com/getvmio/free-javascript-resources)\n- [Free HTML Resources](https://github.com/getvmio/free-html-resources)\n- [Free R Resources](https://github.com/getvmio/free-r-resources)\n- [Free Java Resources](https://github.com/getvmio/free-java-resources)\n- [Free Neural Networks Resources](https://github.com/getvmio/free-neural-networks-resources)\n- [Free Natural Language Processing Resources](https://github.com/getvmio/free-natural-language-processing-resources)\n- [Free Computer Science Resources](https://github.com/getvmio/free-computer-science-resources)\n- [Free React Resources](https://github.com/getvmio/free-react-resources)\n- [Free Security Resources](https://github.com/getvmio/free-security-resources)\n- [Free Node.js Resources](https://github.com/getvmio/free-node-js-resources)\n- [Free PyTorch Resources](https://github.com/getvmio/free-pytorch-resources)\n- [Free Computer Architecture Resources](https://github.com/getvmio/free-computer-architecture-resources)\n- [Free Functional Programming Resources](https://github.com/getvmio/free-functional-programming-resources)\n- [Free Operating System Resources](https://github.com/getvmio/free-operating-system-resources)\n- [Free Cryptography Resources](https://github.com/getvmio/free-cryptography-resources)\n- [Free Compiler Resources](https://github.com/getvmio/free-compiler-resources)\n- [Free Blockchain Resources](https://github.com/getvmio/free-blockchain-resources)\n- [Free SQL Resources](https://github.com/getvmio/free-sql-resources)\n- [Free Python Resources](https://github.com/getvmio/free-python-resources)\n- [Free Unix Resources](https://github.com/getvmio/free-unix-resources)\n- [Free Programming Resources](https://github.com/getvmio/free-programming-resources)\n- [Free Object-Oriented Programming Resources](https://github.com/getvmio/free-object-oriented-programming-resources)\n- [Free CSS Resources](https://github.com/getvmio/free-css-resources)\n- [Free Machine Learning Resources](https://github.com/getvmio/free-machine-learning-resources)\n- [Free Web Development Resources](https://github.com/getvmio/free-web-development-resources)\n- [Free Shell Scripting Resources](https://github.com/getvmio/free-shell-scripting-resources)\n- [Free Rust Resources](https://github.com/getvmio/free-rust-resources)\n- [Free Haskell Resources](https://github.com/getvmio/free-haskell-resources)\n- [Free Software Development Resources](https://github.com/getvmio/free-software-development-resources)\n- [Free Data Science Resources](https://github.com/getvmio/free-data-science-resources)\n- [Free Git Resources](https://github.com/getvmio/free-git-resources)\n- [Free Networking Resources](https://github.com/getvmio/free-networking-resources)\n- [Free Game Development Resources](https://github.com/getvmio/free-game-development-resources)\n- [Free Distributed Systems Resources](https://github.com/getvmio/free-distributed-systems-resources)\n- [Free Embedded Systems Resources](https://github.com/getvmio/free-embedded-systems-resources)\n- [Free DevOps Resources](https://github.com/getvmio/free-devops-resources)\n- [Free Docker Resources](https://github.com/getvmio/free-docker-resources)\n- [Free Robotics Resources](https://github.com/getvmio/free-robotics-resources)\n- [Free Computer Vision Resources](https://github.com/getvmio/free-computer-vision-resources)\n- [Free Deep Learning Resources](https://github.com/getvmio/free-deep-learning-resources)\n- [Free Cloud Computing Resources](https://github.com/getvmio/free-cloud-computing-resources)\n- [Free Go Resources](https://github.com/getvmio/free-go-resources)\n- [Free Data Structures Resources](https://github.com/getvmio/free-data-structures-resources)\n- [Free Control Systems Resources](https://github.com/getvmio/free-control-systems-resources)\n- [Free Artificial Intelligence Resources](https://github.com/getvmio/free-artificial-intelligence-resources)\n- [Free Data Analysis Resources](https://github.com/getvmio/free-data-analysis-resources)\n- [Free Ruby Resources](https://github.com/getvmio/free-ruby-resources)\n- [Free C++ Resources](https://github.com/getvmio/free-cpp-resources)\n- [Free Bash Resources](https://github.com/getvmio/free-bash-resources)\n- [Free Cybersecurity Resources](https://github.com/getvmio/free-cybersecurity-resources)\n- [Free Algorithm Resources](https://github.com/getvmio/free-algorithm-resources)\n- [Free Database Resources](https://github.com/getvmio/free-database-resources)\n- [Free C Resources](https://github.com/getvmio/free-c-resources)\n- [Free Version Control Resources](https://github.com/getvmio/free-version-control-resources)\n- [Free Linux Resources](https://github.com/getvmio/free-linux-resources)\n- [Free Computer Graphics Resources](https://github.com/getvmio/free-computer-graphics-resources)\n","funding_links":[],"categories":["More","Other Lists"],"sub_categories":["TeX Lists"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgetvmio%2Ffree-tensorflow-resources","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgetvmio%2Ffree-tensorflow-resources","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgetvmio%2Ffree-tensorflow-resources/lists"}