MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch
Genre: eLearning | Language: English + .VTT | Duration: 4 hour | Size: 1.48 GB
The main algorithms including Q-Learning, SARSA as well as Deep Q-Learning.
What you'll learn
The concepts and fundamentals of reinforcement 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.
Students are assumed to be familiar with python and have some basic knowledge of statistics, and deep learning.
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.