Deep Reinforcement Learning: Hands-on AI Tutorial in Python
- 4 hours on-demand video
- 7 downloadable resources
- 1 coding exercise
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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- 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.
- Develop artificial intelligence applications using reinforcement learning.
- 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, it's relation to artificial intelligence and machine learning, and how we can formulate a problem in the context of reinforcement learning and Markov Decision Process. We cover different fundamental algorithms including Q-Learning, SARSA as well as Deep Q-Learning. We present the whole implementation of two projects from scratch with Q-learning and Deep Q-Network.
- Machine learning and AI enthusiasts and practitioners, data scientists, machine learning engineers.