Rust Miniprojects
Rust is an emerging language that offers extremely fast speed and makes it easy to write safe and performant code. One of my goals when finishing up my MS program was to make a variety of Rust miniprojects to give myself a solid foundation in the language.
As a machine learning enthusiast, I've been very interested in the speed that Rust is able to offer in the context of ML training. One of my focuses in these miniprojects was to build out mini machine learning solutions for a variety of applications. Here are a handful of them:
- A program that generates text based on User input
- An containerized AutoML program that gives info on the best potential models for your data
- A question answering program using BERT
- Hugging Face Model Downloader to ONNX
One of my other goals was to build out mini cloud based solutions. A good example is my Rust - AWS Lambda Handshake Program, which is useful because cold starts are much faster in Rust as compared to other languages - and thus incur less cost over time.
Some other examples of Rust cloud solutions I've made are:
While my main language is Python, I've found Rust has taken over as my main language when I need something to run very fast, replacing my previous favorite C++. It's much more fun to write code in Rust and the compiler is so strict that it's actually quite difficult to write code that doesn't work. I believe Rust will gain a lot of traction in the coming years in the field of DS/ML.