Skip to main content

Deep Reinforcement Learning 2.0

Online Courses Udemy - Deep Reinforcement Learning 2.0, The smartest combination of Deep Q-Learning, Policy Gradient, Actor Critic, and DDPG

Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team | English [Auto]


Students also bought

  • Unsupervised Deep Learning in Python
  • Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)
  • Data Science: Natural Language Processing (NLP) in Python
  • Recommender Systems and Deep Learning in Python
  • Cutting-Edge AI: Deep Reinforcement Learning in Python
  • Ensemble Machine Learning in Python: Random Forest, AdaBoost

Preview this course GET COUPON CODE

Welcome to Deep Reinforcement Learning 2.0!
In this course, we will learn and implement a new incredibly smart AI model, called the Twin-Delayed DDPG, which combines state of the art techniques in Artificial Intelligence including continuous Double Deep Q-Learning, Policy Gradient, and Actor Critic. The model is so strong that for the first time in our courses, we are able to solve the most challenging virtual AI applications (training an ant/spider and a half humanoid to walk and run across a field).
To approach this model the right way, we structured the course in three parts:
Part 1: Fundamentals
In this part we will study all the fundamentals of Artificial Intelligence which will allow you to understand and master the AI of this course. These include Q-Learning, Deep Q-Learning, Policy Gradient, Actor-Critic and more.
Part 2: The Twin-Delayed DDPG Theory
We will study in depth the whole theory behind the model. You will clearly see the whole construction and training process of the AI through a series of clear visualization slides. Not only will you learn the theory in details, but also you will shape up a strong intuition of how the AI learns and works. The fundamentals in Part 1, combined to the very detailed theory of Part 2, will make this highly advanced model accessible to you, and you will eventually be one of the very few people who can master this model.
Part 3: The Twin-Delayed DDPG Implementation
We will implement the model from scratch, step by step, and through interactive sessions, a new feature of this course which will have you practice on many coding exercises while we implement the model. By doing them you will not follow passively the course but very actively, therefore allowing you to effectively improve your skills. And last but not least, we will do the whole implementation on Colaboratory, or Google Colab, which is a totally free and open source AI platform allowing you to code and train some AIs without having any packages to install on your machine. In other words, you can be 100% confident that you press the execute button, the AI will start to train and you will get the videos of the spider and humanoid running in the end.

Free Coupon Discount Udemy Courses
Comment Policy: Please write your comments that match the topic of this page's posts. Comments that contain links will not be displayed until they are approved.
Open Comments
Close comment