| Project Domains | +Mentors | +Project Difficulty | +
|---|---|---|
| Reinforcement learning, OpenAI Gym, TenserFlow/ PyTorch, ML basics | +Aditya Vivekanand | +Medium to Hard | +
Project Description
+ +This project involves building a solid theoretical foundation in RL concepts, implementing key algorithms like Dynamic Programming, Monte Carlo Methods and Policy Gradient Methods, and applying them to different tasks. +By experimenting with advanced techniques such as Double DQN and Actor-Critic methods, you will optimize agent performance and analyze results. +Comprehensive documentation and evaluation will enhance learning and provide insights for future applications, making this project a stepping stone to mastering RL.
+ +Pre-requisites
+ +-
+
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+
Basic Python Programming -> Python One-Shot by FreeCodeCamp
+
+ -
+
Conceptual understanding of Reinforcement Learning -> Playlist on basics of RL
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+
++ +It is recommended that candidates interested in this project go through the above resources. This will give you an advantage over others during interview for this project.
+
References
+ + + +Mentor
+ +Aditya Vivekanand - avivekanand_b22@et.vjti.ac.in
+ +++ +If you have any doubts regarding this project or any difficulty in understanding the pre-requisites videos you reach out to the mentor.
+