Deep Reinforcement Learning

If you don't mind spending money I would recommend the reinforcement learning nanodegree program from Udacity (https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893). It will take you about four months to complete if you are diligent.

It was created by leading practitioners in the field and the learning material is excellent. If you invest in the course and complete it, you will get a large return on your investment. After completing the program you will have four reinforcement learning projects under your belt that you can show future employers.

Thanks a lot for the reply. I did the ML nanodegree last year and reinforcement learning was my fav part. I'll maybe do the DL nanodegree and then this - https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893

Udacity has 1 month free.

Anyone want to do the DRL nano-degree in one month with me?

https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893

I don't know if that is even doable? 15hrs/wk for 4 months to 1 month is 60hrs/week?

https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893 also uses pytorch but is pretty good. Does a good job of teaching the fundamental and practical aspects of deep reinforcement learning. A sample of the projects you will build https://github.com/karanjude/DeepRL

What have you studied in AI? Have you done any deep learning stuff with neural nets in Python?

Reinforcement learning has existed for years, but all of this new game-playing stuff is pretty recent, mostly originating Deepmind's 2015 Atari-playing Deep Q-Network.

While I've never taken this set of courses, I've heard amazing things. Andrew Ng is an amazing professor, and his other Coursera class on Machine Learning is how I got started: https://www.coursera.org/specializations/deep-learning

I have also heard that this is also very thorough but also very difficult: http://course.fast.ai/index.html

If you feel confident in deep learning stuff already, and just want to learn more about deep reinforcement learning, your options are more limited. The field is still pretty new, and it feels like research comes out every month which makes other models obsolete. I don't know of many resources for learning this stuff, but Udacity just announced a new Deep Reinforcement Learning Nanodegree which looks pretty thorough. All of the projects use Unity! The downside is the cost: https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893

Other than the Udacity course, you can try to work through some research papers, or even just ask in /r/learnmachinelearning and /r/reinforcementlearning.

Finally, you can access a huge resource on reinforcement learning through this book (the draft here is free, official amazon release will be later this year): http://incompleteideas.net/book/the-book-2nd.html.

Good luck!

edit: Completely forgot to mention openAI's gym: https://gym.openai.com/ There are a lot of fun little problems you can work on here. I haven't tried any yet, but it looks like a lot of fun.

I found the UC Berkeley RL course to be very well made, and they're free: http://rail.eecs.berkeley.edu/deeprlcourse/resources/. The lecture videos do not have the slides at a weird angle either. I went through most of the lectures of the Fall 2017 version and they were very good. They also have homeworks available if you wish to do them (although you'll have to grade yourself), see http://rail.eecs.berkeley.edu/deeprlcourse-fa17/index.html and https://github.com/berkeleydeeprlcourse/homework

If you want a course with more guided projects, Udacity released their Deep Reinforcement Learning Nanodegree not long ago: https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893 . Note this is a paid program and costs 1000 USD. One of my coworkers is currently taking this course, and he's been positive about it so far (the course has only been out 1-2 months I believe, so it's still early).