Machine-Learning-Notes

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Machine-Learning-Notes

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Notes for several Machine Learning and Deep Learning courses, textbooks, and talks

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# Machine-Learning-Notes
Notes for several Machine Learning and Deep Learning courses and textbooks and talks.

* **Reinforcement Learning Course** - This lecture course is taught by David Silver of Google Deepmind. The lectures can be found on YouTube at this [link](https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT). 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
  
* **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](http://scaledml.org/).

* **Machine Learning: A Probabilistic Perspective Notes** - ML textbook with an emphasis on describing concepts with relation to probability.

* **Elements of Statistical Learning Notes** - Another hard ML textbook with an emphasis on a lot of the math behind traditional ML models.

* **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](https://conferences.oreilly.com/artificial-intelligence/ai-ca).

Machine-Learning-Notes

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