Files

01. Fundamentals of Reinforcement Learning
- .ipynb_checkpoints
- Images
- 1.01. Key Elements of Reinforcement Learning .ipynb
- 1.02. Basic Idea of Reinforcement Learning.ipynb
- 1.03. Reinforcement Learning Algorithm.ipynb
- 1.04. RL agent in the Grid World .ipynb
- 1.05. How RL differs from other ML paradigms?.ipynb
- 1.06. Markov Decision Processes.ipynb
- 1.07. Action space, Policy, Episode and Horizon.ipynb
- 1.08. Return, Discount Factor and Math Essentials.ipynb
- 1.09 Value function and Q function.ipynb
- 1.10. Model-Based and Model-Free Learning .ipynb
- 1.11. Different Types of Environments.ipynb
- 1.12. Applications of Reinforcement Learning.ipynb
- 1.13. Reinforcement Learning Glossary.ipynb
02. A Guide to the Gym Toolkit
03. Bellman Equation and Dynamic Programming
04. Monte Carlo Methods
05. Understanding Temporal Difference Learning
06. Case Study: The MAB Problem
07. Deep learning foundations
08. A primer on TensorFlow
09. Deep Q Network and its Variants
10. Policy Gradient Method
11. Actor Critic Methods - A2C and A3C
12. Learning DDPG, TD3 and SAC
13. TRPO, PPO and ACKTR Methods
14. Distributional Reinforcement Learning
15. Imitation Learning and Inverse RL
16. Deep Reinforcement Learning with Stable Baselines
17. Reinforcement Learning Frontiers
images
pdf
.DS_Store
README.md

01. Fundamentals of Reinforcement Learning

Oct 13, 2020

d022c37 · Oct 13, 2020

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01. Fundamentals of Reinforcement Learning

01. Fundamentals of Reinforcement Learning

Name	Name	Last commit message	Last commit date
parent directory ..
.ipynb_checkpoints	.ipynb_checkpoints	update	Oct 2, 2020
Images	Images	update	Oct 2, 2020
1.01. Key Elements of Reinforcement Learning .ipynb	1.01. Key Elements of Reinforcement Learning .ipynb	update	Oct 2, 2020
1.02. Basic Idea of Reinforcement Learning.ipynb	1.02. Basic Idea of Reinforcement Learning.ipynb	update	Oct 13, 2020
1.03. Reinforcement Learning Algorithm.ipynb	1.03. Reinforcement Learning Algorithm.ipynb	update	Oct 2, 2020
1.04. RL agent in the Grid World .ipynb	1.04. RL agent in the Grid World .ipynb	update	Oct 2, 2020
1.05. How RL differs from other ML paradigms?.ipynb	1.05. How RL differs from other ML paradigms?.ipynb	update	Oct 2, 2020
1.06. Markov Decision Processes.ipynb	1.06. Markov Decision Processes.ipynb	update	Oct 2, 2020
1.07. Action space, Policy, Episode and Horizon.ipynb	1.07. Action space, Policy, Episode and Horizon.ipynb	update	Oct 2, 2020
1.08. Return, Discount Factor and Math Essentials.ipynb	1.08. Return, Discount Factor and Math Essentials.ipynb	update	Oct 2, 2020
1.09 Value function and Q function.ipynb	1.09 Value function and Q function.ipynb	update	Oct 2, 2020
1.10. Model-Based and Model-Free Learning .ipynb	1.10. Model-Based and Model-Free Learning .ipynb	update	Oct 2, 2020
1.11. Different Types of Environments.ipynb	1.11. Different Types of Environments.ipynb	update	Oct 2, 2020
1.12. Applications of Reinforcement Learning.ipynb	1.12. Applications of Reinforcement Learning.ipynb	update	Oct 2, 2020
1.13. Reinforcement Learning Glossary.ipynb	1.13. Reinforcement Learning Glossary.ipynb	update	Oct 2, 2020

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