Artificial Intelligence: Reinforcement Learning in Python
Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising Applications
What you’ll learn
-
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
Requirements
-
Calculus (derivatives)
-
Probability / Markov Models
-
Numpy, Matplotlib
-
Beneficial to have experience with at least a few supervised machine learning methods
-
Gradient descent
-
Good object-oriented programming skills
Who this course is for:
- Anyone who wants to learn about artificial intelligence, data science, machine learning, and deep learning
- Both students and professionals
![JavaScript Coding Interview Questions [with SOLUTIONS]](https://www.tutorialbar.com/wp-content/themes/rehub-theme/images/default/noimage_336_220.png)