Practical Reinforcement Learning

Practical Reinforcement Learning on Coursera by Yandex and Higher School Of Economics (Russia) Probably the first deep course about RL on Coursera.

List Of Free Reinforcement Learning Courses/Resources Online

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1. Reinforcement Learning Offered at Georgia Tech as CS 8803
2. Practical Reinforcement Learning
3. Reinforcement Learning Explained
4. Reinforcement Learning in Finance
5. Introduction to reinforcement learning
6. Deep Reinforcement Learning CS 294-112 at UC Berkeley
7. An introduction to Reinforcement Learning (Medium Article)
8.  Introduction to RL and Immediate RL
9. Introduction to RL

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I’m taking this one right now from Coursera: Practical RL

I like the assignments but the videos dont cover go deep enough into theory for me. I’d still recommend it.

[D] A good RL course/book?

I want to start learning RL. I have good knowledge about ML/DL, but RL is completely new to me. I want to build a RL model for an application. Since I know about ML/DL, I also know about Prob/Stats/Optimization, but only as a CS student. I come up with some courses:

CS234: CS234: Reinforcement Learning Winter 2021 (stanford.edu)

DeepMind (Hado Van Hasselt): Reinforcement Learning 1: Introduction to Reinforcement Learning - YouTube

Another DeepMind (David Silver): RL Course by David Silver - Lecture 1: Introduction to Reinforcement Learning - YouTube

UofA Coursera: https://www.coursera.org/specializations/reinforcement-learning

CS285: http://rail.eecs.berkeley.edu/deeprlcourse/

HSE Coursera: Practical Reinforcement Learning | Coursera

Due to limited time, I can only learn one course, but after that I can visit another one. What course should I start? There should be assignments too so that I can implement the code.

Extra: I also find some books about RL.

- Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series): Sutton, Richard S., Barto, Andrew G.: 9780262039246: Amazon.com: Books

- Reinforcement Learning: Industrial Applications of Intelligent Agents: D., Phil Winder Ph.: 9781098114831: Amazon.com: Books

- Deep Reinforcement Learning Hands-On: Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more, 2nd Edition: Lapan, Maxim: 9781838826994: Amazon.com: Books

If you can pick one, what will you pick?

You don't need a math PhD to get the math in Sutton and Barto. Also, check out Practical RL and Spinning Up in Deep RL

The best one I did was this: https://www.coursera.org/learn/practical-rl

Starts from the bottom, very practical oriented, with great exercises.

Well... there are cheap 'get started' books on amazon. Also, Coursera has a course in Practical Reinforcement Learning (https://www.coursera.org/learn/practical-rl). It is practical - thanks to OpenAI's reinforcement learning gym it's easy to get something going - but it also has some theory, and explains the various forms. That's probably the most engaging AND systematic way to learn. But Coursera is $50 / month, for however long it takes you to get through. They may have a plan for students or other people of limited means.

Data Scientist here, but rather new with Reinforcement Learning (played a bit with Atari games via Gym and the Practical Reinforcement Learning course from HSE - https://www.coursera.org/learn/practical-rl ). If you want to collaborate on the project, I'll be more than happy to help.

If you're looking to learn theory only and you're not interested in real world stuff, you may ignore my comment. Most probably I will get downvoted for this, there are no good sources for learning RL I tried every course out there including and not limited to:

• David Silver's course
• Coursera's reinforcement learning specialization
• Coursera's practical reinforcement learning

All of these courses will keep torturing you with cryptic mathematical formulas that unless you're interested in learning the mathematical foundations, are a waste of time to understand. You don't learn how to drive a car by learning how he expanding combustion gases push the piston, both are 2 completely different things. My advice is learn on a need-basis, look for whatever is necessary to solve the problem at hand and learn how it's done (if the problem requires the use of RL) otherwise, wait for Andrew NG to create a DRL course which I'm sure you don't want to miss.