Reinforcement Learning in 3 Hours | Full Course using Python

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Want to get started with Reinforcement Learning?

This is the course for you!

This course will take you through all of the fundamentals required to get started with reinforcement learning with Python, OpenAI Gym and Stable Baselines. You'll be able to build deep learning powered agents to solve a varying number of RL problems including CartPole, Breakout and CarRacing as well as learning how to build your very own environment!

In this video you'll learn:
1. All the basics to get up and started with Reinforcement Learning
2. How to build custom environments using OpenAI Gym
3. About working on custom projects for Reinforcement Learning

Links Mentioned

Chapters
0:00 - Start
0:23 - Introduction
1:15 - Gameplan
4:24 - RL in a Nutshell
13:30 - 1. Setup Stable Baselines
21:45 - 2. Environments
30:10 - Loading OpenAI Gym Environments
40:00 - Understanding OpenAI Gym Environments
42:58 - 3. Training
51:32 - Train a Reinforcement Learning Model
1:00:00 - Saving and Reloading Environments
1:04:23 - 4. Testing and Evaluation
1:06:35 - Evaluating RL Models
1:09:34 - Testing the Agent
1:15:56 - Viewing Logs in Tensorboard
1:24:50 - Performance Tuning
1:26:31 - 5. Callbacks, Alternate Algorithms, Neural Networks
1:27:39 - Adding Training Callbacks
1:34:44 - Changing Policies
1:38:27 - Changing Algorithms
1:40:29 - 6. Projects
1:41:31 - Project 1 Atari
1:41:51 - Importing Dependencies
1:44:16 - Applying GPU Acceleration with PyTorch
1:45:11 - Testing Atari Environments
1:51:35 - Vectorizing Environments
1:56:48 - Save and Reload Atari Model
1:57:45 - Evaluate and Test Atari RL Model
2:02:16 - Updated Performance
2:06:34 - Project 2 Autonomous Driving
2:06:56 - Installing Dependencies
2:09:27 - Test CarRacing-v0 Environment
2:12:23 - Train Autonomous Driving Agent
2:17:16 - Save and Reload Self Driving model
2:18:20 - Updated Self Driving Performance
2:28:56 - Project 3 Custom Open AI Gym Environments
2:29:35 - Import Dependencies for Custom Environment
2:32:00 - Types of OpenAI Gym Spaces
2:38:47 - Building a Custom Open AI Environment
2:51:49 - Testing a Custom Environment
2:52:49 - Train a RL Model for a Custom Environment
2:56:22 - Save a Custom Environment Model
2:58:49 - 7. Wrap Up

Oh, and don't forget to connect with me!

Happy coding!
Nick

P.s. Let me know how you go and drop a comment if you need a hand!

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Комментарии

thanks man !! you are a superhero for students learning in the field of A.I !

damanpreetsingh

This is one of the best tutorials on Reinforcement Learning I've come across. Nicholas, your channel is superb.

pramanikd

Thanks Nicholas for the time and effort you put for creating this great course! it's really doing a great job bridging the gap between theoretical and practical.

ereztison

I cannot tell you lucky I am that I found this channel. Awesome content. Awesome delivery and a overall amazing person.
Thanks a lot for putting so much effort in all the videos.

krutyanjayshinde

This is the most charming video for beginer learning RL I have watched so far!! Thank you very much!!

rixinxie

Hi Nicholas, thank you very much for your precious time to make us understand the every single step involved in RL. Your tutorials help me a lot. Keep posting such tutorials.🙂

pavaniddalagi

What you are doing on your channel is nothing short of awesome. With the expected growth in the field of A.I. and machine learning there's a clear path to this being the most subscribed/watched educational channel on the subject. Thank you and looking forward to what you come out with next

jveeck

Over the summer, I did a research project with a professor at my college over Reinforcement Learning in which both of us were not well versed in the subject. Your videos have helped me out immensely with being able to get a custom environment up.

tohbs

A perfect Kickstarter for absolute beginners. Thanks for the video!

suryavenkatesan

super clear, super beginner friendly and learned tons of super useful tools and info, THANK YOU! Nicholas

siyuancheng

What an amazing content! Took me about a week to go through the whole video 😅Totally worth it though! Appreciate the effort put into this and your other videos as well. Coding is not my strongest point so it's nice to see someone explain everything in detail!

victorpessanha

Amazing channel my dude, great quality videos. Your passion for data science makes me really excited to learn a bunch of new things.

jjhj_

Excellent explanation on practical approach to RL!! Thanks a lot, Nic! Love from India!

rhari

I really appreciate you making this content! Well done and thank you!

davidjhyatt

dude, you are the best. You deserve a medal.

atphamthanh

This is the video we were looking for the long. Thanks a lot!

yogeshporwal

Hi Nicholas, I am norwegian so as normal I have some limitations regarding deep language articulation. Therefore I can not sufficiently express my impression about your effort. There is no words in dictionary to formulate your outstanding scarification and willingness to share you passion and knowledge among others. Beside regarding domain is known for me It is always pleasure to hear from you. Yes, from my humble point of view you and your channel are the pearls, who secure only impressive performance. I do need to wish you nothing mores since I know you achieve all your goals! Have a nice day!

markusbuchholz

This is super cool high quality content! the best video about practical start in reinforcement learning I ever saw :) Thank you!

timurnurlygayanov

I don't have words to thank you for this AMAZING course. After this video I could finally start walking by myself on machine learning. You are a hero, man... thanks a LOT!!!

And you have so many great other videos on your channel... God bless you!!

guilhermetogniolo

Thanks a lot Nic! Excellent guide for beginners. Greetings from Colombia!

felipearenasuribe

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