Reinforcement Learning

Dive into the world of Reinforcement Learning through this comprehensive 3.5-hour tutorial series. Begin with an introduction to Q Learning and its table-based approach, then progress to understanding the Q Learning algorithm and agent implementation. Analyze the Q-Learning agent's performance before learning how to create a custom Reinforcement Learning (RL) environment. Advance to Deep Q Learning with DQN, and finally, master the techniques for training and testing a Deep reinforcement learning (DQN) agent. Gain practical knowledge and hands-on experience in this cutting-edge field of artificial intelligence.

Syllabus

Q Learning Intro/Table - Reinforcement Learning p.1.
Q Learning Algorithm and Agent - Reinforcement Learning p.2.
Q-Learning Agent Analysis - Reinforcement Learning p.3.
Creating A Reinforcement Learning (RL) Environment - Reinforcement Learning p.4.
Deep Q Learning w/ DQN - Reinforcement Learning p.5.
Training & Testing Deep reinforcement learning (DQN) Agent - Reinforcement Learning p.6.

Taught by

sentdex

Reviews

4.3 rating, based on 3 Class Central reviews

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Moulya Reddy

This YouTube course on Reinforcement Learning is very well explained with clear examples and practical demonstrations. The instructor breaks down complex concepts like Q-learning, policy gradients, and Markov Decision Processes into simple, understandable parts. The visualizations and code walkthroughs make learning easier and engaging. Great resource for beginners and intermediate learners!
Harini Sreeramadasu

it is a great course. very beginner-friendly. would definitely recommend it to people . there was this fun way of teaching the whole time in the video.
P CHANDRA SEKHAR

Good explanation of this reinforcement learning classes and iam very well to understanding this classes

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