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awesome-ml-courses
Awesome free machine learning and AI courses with video lectures.
https://github.com/luspr/awesome-ml-courses
Last synced: 1 day ago
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Introductory Lectures
- Machine Learning (Stanford CS229) - autumn2018.html)
- Convolutional Neural Networks for Visual Recognition (Stanford CS231n)
- Introduction to Artificial Intelligence (UC Berkeley CS188)
- Applied Machine Learning 2020 (Columbia)
- Introduction to Reinforcement learning with David Silver (DeepMind)
- Machine Learning (Stanford CS229) - autumn2018.html)
- Introduction to Artificial Intelligence (UC Berkeley CS188)
- Applied Machine Learning 2020 (Columbia)
- Introduction to Reinforcement learning with David Silver (DeepMind)
- Machine Learning with Graphs (Stanford CS224W)
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Advanced Lectures
- Deep Unsupervised Learning (UC Berkeley CS294) - cs294-158-sp19/home)
- Frontiers of Deep Learning (Simons Institute) - 1)
- New Deep Learning Techniques - deep-learning-techniques/?tab=overview)
- Geometry of Deep Learning (Microsoft Research) - us/research/event/ai-institute-2019/)
- Deep Multi-Task and Meta Learning (Stanford CS330)
- Mathematics of Machine Learning Summer School 2019 (University of Washington)
- Probabilistic Graphical Models (Carneggie Mellon University) - spring-2019/)
- Probabilistic and Statistical Machine Learning 2020 (University of Tübingen)
- Statistical Machine Learning 2020 (University of Tübingen)
- Mobile Sensing and Robotics 2019 (Bonn University)
- Sensors and State Estimation Course 2020 (Bonn University)
- Photogrammetry 2015 (Bonn University)
- Advanced Deep Learning & Reinforcement Learning 2020 (DeepMind / UCL)
- Data-Driven Dynamical Systems with Machine Learning
- Data-Driven Control with Machine Learning
- ECE AI Seminar Series 2020 (NYU)
- CS287 Advanced Robotics at UC Berkeley Fall 2019
- CSEP 546 - Machine Learning (AU 2019) (U of Washington)
- Deep Reinforcment Learning, Decision Making and Control (UC Berkeley CS285)
- Stanford Convex Optimization
- Full Stack Deep Learning 2019
- Emerging Challenges in Deep Learning
- Deep|Bayes 2019 Summer School
- New Directions in Reinforcement Learning and Control (Institure for Advanced Study)
- Workshop on Theory of Deep Learning: Where next (Institure for Advanced Study)
- Deep Learning: Alchemy or Science? (Institure for Advanced Study)
- Theoretical Machine Learning Lecture Series (Institure for Advanced Study)
- Mathematics of Big Data and Machine Learning (MIT)
- Introduction to Data-Centric AI (MIT) - ZnEU0yNJ1mo5) | [Lab assignments](https://github.com/dcai-course/dcai-lab)
- Probabilistic Graphical Models (Carneggie Mellon University) - spring-2019/)
- Probabilistic and Statistical Machine Learning 2020 (University of Tübingen)
- Statistical Machine Learning 2020 (University of Tübingen)
- Data-Driven Dynamical Systems with Machine Learning
- Data-Driven Control with Machine Learning
- ECE AI Seminar Series 2020 (NYU)
- CS287 Advanced Robotics at UC Berkeley Fall 2019
- CSEP 546 - Machine Learning (AU 2019) (U of Washington)
- Stanford Convex Optimization
- New Directions in Reinforcement Learning and Control (Institure for Advanced Study)
- Theoretical Machine Learning Lecture Series (Institure for Advanced Study)
- Mathematics of Big Data and Machine Learning (MIT)
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