From 72bc3cde1682c3740c4d974655041e94da227159 Mon Sep 17 00:00:00 2001 From: Aditya Vivekanand <142730385+adityavivekanand@users.noreply.github.com> Date: Wed, 12 Jun 2024 15:33:34 +0530 Subject: [PATCH 1/3] Create GymMaster.md GymMaster PR --- _projects/GymMaster.md | 36 ++++++++++++++++++++++++++++++++++++ 1 file changed, 36 insertions(+) create mode 100644 _projects/GymMaster.md diff --git a/_projects/GymMaster.md b/_projects/GymMaster.md new file mode 100644 index 0000000..1b33d83 --- /dev/null +++ b/_projects/GymMaster.md @@ -0,0 +1,36 @@ +--- +Layout: Page +Title: GymMaster +Description: Project to gain a deep understanding of Reinforcement Learning (RL) by systematically exploring and solving various OpenAI Gym environments. +--- + +| 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](https://www.youtube.com/watch?v=rfscVS0vtbw) + +- Conceptual understanding of Reinforcement Learning -> [Playlist on basics of RL](https://www.youtube.com/watch?v=JgvyzIkgxF0) + +> 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 + +- [OpenAI Gym Document](https://www.gymlibrary.dev/content/basic_usage/) +- [Sutton and Barto](https://www.google.co.in/books/edition/Reinforcement_Learning_second_edition/uWV0DwAAQBAJ?hl=en&gbpv=1&printsec=frontcover) + +### 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. From eee299ee5b8951b21f9ab4b833ecf51b15be922f Mon Sep 17 00:00:00 2001 From: Aditya Vivekanand <142730385+adityavivekanand@users.noreply.github.com> Date: Wed, 12 Jun 2024 15:59:32 +0530 Subject: [PATCH 2/3] Create GymMaster.html GymMaster Site --- _site/projects/GymMaster/GymMaster.html | 296 ++++++++++++++++++++++++ 1 file changed, 296 insertions(+) create mode 100644 _site/projects/GymMaster/GymMaster.html diff --git a/_site/projects/GymMaster/GymMaster.html b/_site/projects/GymMaster/GymMaster.html new file mode 100644 index 0000000..2dd0fce --- /dev/null +++ b/_site/projects/GymMaster/GymMaster.html @@ -0,0 +1,296 @@ + + + + + + + + + + + + + GymMaster | Eklavya 2024 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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GymMaster

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GymMaster is a project to gain a deep understanding of reinforcement learning (RL) by systematically exploring and solving various OpenAI Gym environments.

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Project DomainsMentorsProject Difficulty
Reinforcement learning, OpenAI Gym, TenserFlow/ PyTorch, Machine LearningAditya VivekanandMedium - Hard
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Project Description

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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.

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Pre-requisites

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Basic Python Programming
+Reinforcement Learning Basics
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Resources

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OpenAI Gym Documentation
+Sutton and Barto- Book on Reinforcement Learning
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convolutions on FPGA

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Reinforcement Learning

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To understand and explore Reinforcement LEarning through OpenAI Gym's environments.

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