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free-deep-learning-resources

[Deep Learning Free Resources] This repository collects 76 of free resources for Deep Learning. 🧠 Plumb the depths of AI with our Deep Learning Nexus repository! Explore a comprehensive collection of free resources on neural networks and deep learning architectures. With our online Playground, im...
https://github.com/getvmio/free-deep-learning-resources

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Resources
- UvA Deep Learning Course
- Deep Learning Analysis - on experience with implementing and training deep neural networks. |
- Theories of Deep Learning
- Applied Deep Learning 2022 - on experience in implementing and deploying deep learning models for real-world applications. |
- Machine Learning Specialization
- Deep Learning Fundamentals
- Deep Multi-Task and Meta Learning - depth understanding of state-of-the-art multi-task learning and meta-learning algorithms for few-shot learning, transfer learning, and lifelong learning. |
- Deep Learning - on experience in PyTorch. Prepare to understand and extend the current literature on deep learning. |
- Machine Learning: Intro to Statistical Learning - on practical sessions using Torch deep learning framework. |
- Convolutional Neural Networks for Visual Recognition
- Deep Learning for Natural Language Processing - 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. |
- Introduction to Machine Learning
- Tensorflow for Deep Learning Research
- Deep Learning for Natural Language Processing
- Deep Learning For Visual Computing
- Deep Learning for Computer Vision - based deep learning methods for visual recognition tasks, including image classification and object detection. |
- A Selective Overview of Deep Learning
- Deep Learning
- High-Level Vision - on experience with state-of-the-art algorithms and real-world applications. |
- Advanced Computer Vision - edge computer vision algorithms, deep learning techniques, and real-world applications. |
- Geometric Deep Learning - on experience and real-world applications. |
- Neural Networks: Zero to Hero
- Deep Learning CMU - led video lectures from Carnegie Mellon University. Dive into neural networks, CNN, RNN, and more. |
- Deep Learning Systems - on implementation of key concepts. |
- Neural Networks and Applications - world applications in image recognition, NLP, and predictive modeling. |
- Deep Learning
- Intermediate Deep Learning - on experience with cutting-edge models and applications. |
- Neural Networks for Machine Learning - on coding exercises. |
- Practical Deep Learning for Coders - world problems with this free course from fast.ai. Build and train models for computer vision, NLP, and more. |
- Deep Learning from the Foundations - of-the-art models from scratch with fast.ai Part 2. |
- Deep Learning for Artificial Intelligence - world applications in AI, offered by Universitat Politècnica de Catalunya (UPC) in Barcelona. |
- Deep Learning for Computer Vision - of-the-art models for image and video analysis. |
- Deep Learning: CS 182 - depth course, covering neural networks, optimization, and real-world applications in computer vision, NLP, and more. |
- Deep Unsupervised Learning - on implementation and application of cutting-edge techniques. |
- Deep Unsupervised Learning - on experience and exposure to cutting-edge research. |
- Nvidia Machine Learning Class - world examples. |
- Deep Unsupervised Learning - edge deep learning techniques in generative models and self-supervised learning. Taught by renowned instructors at UC Berkeley. |
- Deep Learning for Self-Driving Cars - depth knowledge in this cutting-edge field. |
- Deep Learning at Oxford 2015 - on demonstrations and code examples, suitable for beginners and advanced learners. |
- NYU Deep Learning
- Introduction to Deep Learning - edge topics in computer vision, natural language processing, and more. |
- Deep Learning Course - on implementation. Taught by experienced instructor from New York University. |
- Intro to Deep Learning & Generative Models - on tutorials using TensorFlow and PyTorch. |
- Deep Learning for Computer Vision
- Deep Learning - on implementation experience. Taught by experienced instructors from Stanford University. |
- Designing, Visualizing & Understanding Deep Neural Networks
- Deep Learning - on projects and experienced instructors. |
- Deep Learning - world applications. Hands-on coding and experienced instructors. |
- Full Stack DL Bootcamp 2019 - of-the-art models. Hands-on experience in building and deploying real-world deep learning applications. |
- Deep Learning - on exercises using popular frameworks like TensorFlow and PyTorch. |
- Deep Multi-Task & Meta Learning - 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. |
- Deep Multi-Task & Meta Learning I - of-the-art multi-task learning and meta-learning algorithms in this graduate-level course, preparing you for research in deep learning. |
- Machine Learning - world applications. |
- Advanced Introduction to Machine Learning - depth exploration of fundamental machine learning concepts and techniques, including deep learning, clustering, kernel machines, and graphical models. |
- Deep Reinforcement Learning & Control - on experience and tackle complex decision-making problems. |
- Introduction to Machine Learning - world applications. Free online video lectures. |
- Machine Learning Course
- Efficient Machine Learning
- Advanced Machine Learning
- PURDUE Machine Learning Summer School 2011 - on exercises and access to valuable resources. |
- Introduction to Machine Learning
- Deep Reinforcement Learning - on experience and expert guidance from UC Berkeley's CS 285 course. |
- Advanced Deep Learning
- Speech Recognition and Understanding
- Machine Learning - on experience with real-world datasets and projects, taught by an expert in the field, Bert Huang. |
- Mediterranean Machine Learning Summer School 2023 - on workshops, expert instruction, and networking opportunities in a scenic Mediterranean location. |
- Microsoft Research
- Advanced Introduction to Machine Learning - on experience with real-world projects, and exposure to the latest advancements in deep learning and reinforcement learning. |
- Deep Reinforcement Learning - on assignments and projects to apply the concepts. |
- Deep Reinforcement Learning Bootcamp - on demos and code examples. |
- Deep Learning for Natural Language Processing - edge techniques. |
- Natural Language Processing with Deep Learning - edge neural networks for natural language processing and the latest advancements in large language models. |
- Recent Advances on Foundation Models - level course at the University of Waterloo. |
- Autonomous Vehicle System Engineering - on projects and simulations for practical experience. |
- DeepRob Winter 2023 - on experience. |
- Deep Generative Models I - based models. Gain hands-on experience and insights into the latest research in this rapidly evolving field. |
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