Rust + Machine Learning: 006
This is part of my participation in the #100DaysOfCode challenge. This round, I’m learning Rust and Machine Learning (ML) and developing violette: a portable ML system and JavaScript API in Rust.
When I first started learning to code, I had an inordinate amount of time on my hands. Jumping into #100DaysOfCode back then was easy. One hour a day? Psssh. Make it three to four. I would do freeCodeCamp exercises for an hour or so, and then I’d read all things JS I could get my hands on.
Now, I’m having to carve out time to participate. I run a small on- and offline fitness business. I manage a software development project. I’m collaborating on a podcast and a book. And somehow I’m supposed to have a social life?
And then to top it all off, I want to do this Rust and machine learning (ML) shit.
Yesterday, I was redesigning a landing page for an upcoming marketing campaign I’m doing in collaboration with a local brewery at which I teach yoga on the weekends. I then had to create, write, and schedule my company’s weekly newsletter. This was all after a morning hike with my partner and her friends. When all was completed, I had a small window of opportunity to dive into Rust before our evening plans came up.
I managed to finish working through chapter three of The Rust Programming Language. The chapter was fairly dense, but as I’m coming from another programming language, most of the content was easily accessible and portable. Tuples and static-length arrays are new for me, though destructuring is not. Type annotations aren’t new for me, though the -> i32 {} syntax is. It’s the subtle differences in types that I’ll have to pay close attention to until I feel familiar enough with language.
It was an hour and a half of work, but I managed to knock it out before we left for the evening. The next 94 days are going to be … interesting.
006/100
