There is No Spoon. A software engineers primer for demystified ML

jmatthews

This is my weekend project. I am building up my pattern recognition in machine learning. By that I mean see X problem, instantly think of Y solution. The primer markdown file is the artifact of that exploration. read it from top to bottom or better have your favorite language model read it and then explore the space with a strong guided syllabus.

oleggromov

Thank you for sharing! Saved to bookmarks to read on my free time. Hopefully I'll get some soon :)

janalsncm

I personally think it is much more important to have strong statistical intuitions rather than intuitions about what neural networks are doing. The latter isn’t wrong or useless. It’s simply not something a typical software engineer will need. On the other hand, wiring up LLMs into an application is very popular and may be an engineer’s first experience with systems that are fundamentally chaotic. Knowing the difference between precision and recall and when you care about them will get you a lot more bang for your buck. I would suggest the gateway drug into ML for most engineers is something like: we have a task and it can currently be done for X dollars. But maybe we can do it for a tenth of the price with a different API call. Or maybe there’s something on Huggingface that does the same thing for a fixed hourly cost, hundreds of times cheaper in practice.

bonoboTP

Just read a good textbook instead of this LLM-written stuff. For example those by Murphy or Prince or Bishop. Or one of many YouTube lecture series from MIT or Stanford. There are many primer 101 tutorials and Medium posts. But if you actually want to learn instead of procrastinating, pick up a real textbook or work through a course.

whoamii

Feature request for HN, Adblocker, etc: please block pages with the text “it isn’t X, it is Y”.

zar1048576

Nice weekend project! Even though there are copious resources out there (textbooks, videos, etc.), those may not appeal to everyone. People have different preferred modalities for consuming information and there is always value in (correctly) reframing concepts in a way that can be better understood by people who don’t resonate with traditional textbooks and YouTube videos. I’m glad you found a formulation that works for you, and judging by the number of upvotes, it resonated with others as well. At the very least, I’m sure that working on this improved your understanding as well!

hilliardfarmer

Please stop trying to trick us into reading AI generated text. "This isn't a textbook or a tutorial. It's a mental model — the abstractions you need to reason about ML systems the way you already reason about software systems."