Reinforcement Learning: The Complete Course in 2022
Complete guide to Reinforcement Learning, with MAB problems, Games, Taxi problems, and Online Advertising Applications
4.51 (86 reviews)
509
students
19.5 hours
content
Nov 2021
last update
$13.99
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What you will learn
Policy gradient algorithm
Markov Chain
Policy iteration algorithm
Monte Carlo method
Q-Learning
Deep-Q networks
Double Deep-Q networks
SARSA algorithm
Duelling Deep-Q networks
REINFORCE algorithm
Actor-critic algorithm
Understand a cutting-edge implementation of the A2C algorithm (OpenAI Baselines)
Deep Recurrent Q-Learning algorithm and DRQN agent Implementation
Asynchronous Advantage Actor-Critic algorithm and A3C agent Implementation
Proximal Policy Optimization algorithm and PPO agent Implementation
Deep Deterministic Policy Gradient algorithm and DDPG agent Implementation
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3831272
udemy ID
07/02/2021
course created date
12/03/2021
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