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Believe it or not, Reinforcement Learning is the way to the future. That's why we are happy to present to you this series which gets you from zero to hero in RL. In this series, we will solve very interesting problems with Deep Reinforcement Learning. Since no learning can occur without knowing its basic principles, we dedicate some of the initial videos to classical Reinforcement Learning. But soon, we will start coding out RL agents that can amaze you with what they can do. This video introduces you to the formal components of a Reinforcement Learning System. Links: Lunar Lander Environment: https://www.gymlibrary.ml/environments/box2d/lunar_lander/ Reinforcement Learning Book by Sutton and Barto: http://incompleteideas.net/book/the-book.html Free Reinforcement Learning Course from IIT Madras: https://nptel.ac.in/courses/106106143 Music: https://www.bensound.com/ Visuals: https://www.pexels.com/ ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science! 💭Share your thoughts, experiences, or questions in the comments below. I love hearing from you! Timestamps: 0:00 - Intro 1:01 - How we learn 2:26 - Why is RL a big deal 4:04 - Elements in RL 7:27 - A Simple Example 8:52 - Environments 10:38 - Rewards 11:05 - Policy 11:48 - Value 13:39 - Formalization 14:27 - Outro
