dezero_rs

dezero_rs is a Rust-based clone of the dezero framework, originally designed for deep learning experiments. This project is primarily an educational endeavor aimed at understanding and implementing deep learning frameworks in Rust. It serves as an experimental platform for my personal learning and exploration of both Rust programming and deep learning concepts.

Purpose

• Educational: The primary goal of dezero_rs is educational. It is a means for me to dive deep into the intricacies of deep learning frameworks and how they can be implemented in a systems programming language like Rust.
• Experimental: This project is experimental in nature. It allows for exploration of new ideas and techniques in the context of deep learning and Rust programming.

Features

• Pure Rust Implementation: dezero_rs is built entirely in Rust, aiming to leverage the language's safety and performance characteristics for educational purposes.

Current Limitations

• Performance: The manual implementation of linear algebra components results in performance issues, particularly in computation-intensive tasks. This limitation is acknowledged and accepted in the context of the project's educational objectives.

Contributions

While dezero_rs is primarily for my personal educational purposes, contributions are welcome, especially from those interested in learning alongside me or offering insights that could enhance the project's educational value:

• Educational Enhancements: Suggestions that improve the understanding of deep learning or Rust programming.
• Performance Optimization: Contributions that address performance bottlenecks without compromising the project's educational goals.
• Feature Expansion: Adding features to more closely align with the original dezero framework's capabilities, enriching the learning experience.

Gallery

Linear Regression

Quadratic Regression

Sin Regression

MNIST

License

dezero_rs is released under the MIT License.