| 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
-
Basic Python Programming -> Python One-Shot by FreeCodeCamp
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Conceptual understanding of Reinforcement Learning -> Playlist on basics of RL
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 - [email protected]
If you have any doubts regarding this project or any difficulty in understanding the pre-requisites videos you reach out to the mentor.