Notes for several Machine Learning and Deep Learning courses and textbooks and talks.
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Reinforcement Learning Course - This lecture course is taught by David Silver of Google Deepmind. The lectures can be found on YouTube at this link. In this course, you'll learn about the following topics.
- Markov Decision Processes
- Value functions
- Policies
- Dynamic programming approaches
- Monte Carlo learning
- Temporal difference learning
- SARSA
- Value function approximation
- Policy gradients
- Deep Q networks
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Scaled Machine Learning Conference Notes - These were the notes I took at the Scaled ML conference at Stanford. Here is a link to event page.
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Machine Learning: A Probabilistic Perspective Notes - ML textbook with an emphasis on describing concepts with relation to probability.
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Elements of Statistical Learning Notes - Another hard ML textbook with an emphasis on a lot of the math behind traditional ML models.
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The AI Conference 2017 Notes - These were the notes I took at The AI Conference sponsored by O'Reilly Media. Here is a link to event page.