Deep Reinforcement Learning A Hands on Tutorial in Python

Deep Reinforcement Learning: A Hands-on Tutorial in Python
.MP4 | Video: 1280×720, 30 fps(r) | Audio: AAC, 48000 Hz, 2ch | 1.48 GB
Duration: 4 hours | Genre: eLearning | Language: English
Learn the highly in-demand skill of Reinforcement Learning in a simple and practical way using Python and Keras.

What you’ll learn

The concepts and fundamentals of reinforcement learning
The main algorithms including Q-Learning, SARSA as well as Deep Q-Learning.
How to formulate a problem in the context of reinforcement learning and MDP.
Apply the learned techniques to some hands-on experiments and real world projects.

Requirements

Students are assumed to be familiar with python and have some basic knowledge of statistics, and deep learning.

Description

In this course we learn the concepts and fundamentals of reinforcement learning, and how we can formulate a problem in the context of reinforcement learning and Markov Decision Process. We cover different algorithms including Q-Learning, SARSA as well as Deep Q-Learning. We present the whole implementation of two projects with Q-learning and Deep Q-Network.

Who this course is for:

Machine learning and AI enthusiasts and practitioners, data scientists, machine learning engineers.

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