About This Video
"Code a Reinforcement Learning Library in C from Scratch (Full Course)" is a trending video in the **Food** category on YouTube that has caught the attention of viewers and creators alike.
Video Description
Learn how to build a complete reinforcement learning framework from scratch in C. The course begins with constructing a custom computational graph and automatic differentiation (autograd) engine to handle matrix operations alongside forward and backward passes. It then walks through developing a standalone Snake game environment from the ground up, including custom state vector encoding and collision reward logic. Finally, the lesson ties everything together by implementing the REINFORCE policy gradient algorithm, trajectory rollouts, and an end-to-end training pipeline to train the agent.
💻 Code:
✏️ Course created by @harshbhatt7585
socials:
Twitter:
Insta: harshbhatt.ai
⭐️ Chapters ⭐️
- Introduction & Overview
- Setting Up the Autograd Engine & Variables
- Matrix Creation & Allocation Logic
- Building Nodes & Computational Graph Traversal
- Forward & Backward Activation Operations
- Matrix Multiplication (Row-Major & Transpose Operations)
- Building the Snake Game RL Environment
- State Vector Encoding & Reward System
- Training Pipeline & Rollout Buffers Setup
- Implementing the Actor-Critic Model
- Computing Returns, Advantages & Backward Pass
- Optimizer Step, Evaluation & Conclusion
❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning:
🎉 Thanks to our Champion and Sponsor supporters:
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Key Points
- ✏️ Course created by @harshbhatt7585
- Insta: harshbhatt.ai
- Introduction & Overview
- Setting Up the Autograd Engine & Variables
- Matrix Creation & Allocation Logic
Why This Is Trending
This food video is gaining traction on YouTube. Content creators in the food space can explore similar topics to engage their audience.
