Artificial Intelligence: Reinforcement Learning in Python
Artificial Intelligence: Reinforcement Learning in Python Course
Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising Applications
This Artificial Intelligence: Reinforcement Learning in Python Course is a complete guide to reinforcement learning, with stock trading and online advertising applications. It is created by Lazy Programmer Team and Lazy Programmer Inc. The course covers 17 different reinforcement learning algorithms, including Q-Learning and SARSA. It also teaches you how to apply gradient-based supervised machine learning methods to reinforcement learning.
The Artificial Intelligence: Reinforcement Learning in Python Course is structured in a way that makes complex concepts simple and easy to understand. It includes over 40 real-life demos of tasks being performed using OpenAI Gym, with zero code changes. The lectures are short, with most being between 5-15 minutes long.
The Artificial Intelligence: Reinforcement Learning in Python Course covers a wide range of topics, including the multi-armed bandit problem and the explore-exploit dilemma, Markov Decision Processes (MDPs), Dynamic Programming, Monte Carlo Temporal Difference (TD) Learning, Approximation Methods (i.e., how to plug in a deep neural network or other differentiable model into your RL algorithm), and more.
The course is rated 4.7 out of 5 stars by 9,754 students on Udemy. It has been taken by over 44,736 students so far. The course is fully optimized and comes with a certificate of completion.
What you’ll learn in Artificial Intelligence: Reinforcement Learning in Python Course
- Apply gradient-based supervised machine learning methods to reinforcement learning.
- Understand reinforcement learning on a technical level.
- Understand the relationship between reinforcement learning and psychology.
- Implement 17 different reinforcement learning algorithms.
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