Reinforcement Learning with Python Explained for Beginners [Video]

By AI Sciences
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  1. Introduction to Course and Instructor

About this video

Although introduced academically decades ago, the recent developments in the field of reinforcement learning have been phenomenal. Domains such as self-driving cars, natural language processing, healthcare industry, online recommender systems, and so on have already seen how RL-based AI agents can bring tremendous gains.

This course will help you get started with reinforcement learning first by establishing the motivation for this field and then covering all the essential topics, such as Markov Decision Processes, policy and rewards, model-free learning, temporal difference learning, and so on.

Each topic is accompanied by exercises and complementing analysis to help you gain practical and tangible coding skills.

By the end of this course, not only will you have gained the necessary understanding to implement RL in your projects but also implemented an actual Frozenlake project using the OpenAI Gym toolkit.

All resources and code files are placed here:

Publication date:
February 2021
9 hours 7 minutes

About the Author

  • AI Sciences

    The AI Sciences Team is a group of experts, PhDs, and practitioners of artificial intelligence, computer science, machine learning, and statistics. Some of them work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.

    They have produced a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of machine learning, statistics, artificial intelligence, and data science.

    Their courses have had phenomenal success and have helped more than 100,000 students master AI and data science.

    Browse publications by this author
Reinforcement Learning with Python Explained for Beginners [Video]
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