Reinforcement Learning Tutorials for the African Masters of Machine Intelligence
This repo includes lecture slides, notebooks and other material for the RL week at AMMI, the African Masters of Machine Intelligence
Dynamic Programming
Lec 1: From basic concepts to deep Q-networks
Extra:
- Supplementary: Policy/Value Iteration in Matrix form
- RL book Chapter 4, Dynamic Programming
- Dynamic Programming lecture video
Monte Carlo and TD learning
Policy Gradient
(git) Update local repo
To update your local repository (repo) without losing your personal changes to the files use...
git pull --rebase --autostash
Questions
- To communicate directly with the tutors, chat to us here: https://www.tinyurl.com/chat-to-us
- To put a question forward to the tutors and your peers, open an 'issue' with the label 'question' example-clickMe
Addtional general resources
Book
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('^__^') Sutton and Barto (4.7/5)
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Solutions
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Chap 1 - 9 ( /5)
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Chap 1,2, 13 (with summaries) ( /5)
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Chap 1-3 (with code) ( /5)
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Chap 1-3 (with code) ( /5)
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Code (of content)
- Chap 1 - 13, Python ( /5)
- Chap 1 - 13, Lisp ( /5)
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('^__^') An Introduction to Deep Reinforcement Learning(/5)
Course
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(^_^) Wild ML (Denny Britz) - Meta-course (recommended reading, exercises from other courses, implementations) with implementations, Python ( /5)
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(^_^) Dave Silver ( /5)
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(-)Coursera - Practical RL ( /5)
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(^_^) Coursera - University of Alberta - 4 part specialization (3/5)
Video
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(",) Udacity
Really great playlist of videos 5min each about 200 of them - well labelled, so that if you want to find a specific thing to learn / revise it is easy to find - very comprehensive - give it a look I reckon
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(^_^) Deeplizard - RL playlist - 18 Vids ( /5)
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(^_^) YouTube playlist ( /5)
Articles
- (",) Free code camp - ( 4/5) - good overview
- (",) Medium, RL algorithm review (3/5)
- (",) Medium, RL overview (3/5)
- (",) Summary of terminology (3.5/5)
Lectures
Survey
- (",) overviews of contemporary RL

