6 Practice Certification Exams *110 Questions with full explanations* Most Expected CEH (312-50) Exam Practice Questions
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.
- 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.
- Students are assumed to be familiar with python and have some basic knowledge of statistics, and deep learning.
Mehdi MohammadiMachine Learning Engineer
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