A Visual Introduction to Machine Learning (2015)

ayhanfuat

This is from 2015. Both technically and conceptually it was ahead of its time.

Jhater

Josh Starmers books are very visual as well, probably the best source I'd recommend to learn ML https://www.youtube.com/c/joshstarmer https://statquest.org/

cake-rusk

Where's the rest of it?

shardullavekar

has anyone come across an r2d3-style explainer for something as high-dimensional as a Transformer's attention mechanism?

stared

It is a masterpiece! Each time I give an introduction to machine learning, I use this explorable explanation. There is a collection of a few more here: https://p.migdal.pl/interactive-machine-learning-list/

smaili__

So amazing, wish there were more articles like this. I love visual learning. Also reminds me of another blog post: https://pomb.us/build-your-own-react/ , probably not directly the same, but similar-ish written blog posts, easy to stay on track and follow. It is so easy to learn with this kind of blog post.

quickrefio

R2D3 did an amazing job here. It’s rare to see statistical learning concepts explained visually this clearly.

tonyhschu

One of the creators of R2D3 here. Funny to wake up to this today! Happy to answer questions here or on bsky

mvrckhckr

This is still great after more than a decade.

sp4cec0wb0y

Did they not have mobile responsive sites in 2015? Lol

xpe

The balls-from-the-sky sieve-style animation* showing classifications literally falling out of the decision tree is my favorite part. I haven't seen this anywhere else (yet); this visualization technique deserves more percolation (pun intended). (#1) Not even to mention the fact that the animation is controlled by scrolling, which gives an intuitive control over play, pause, rewind, fast-forward, etc. Elegant and brilliant. (#2) Stunningly good also in the sense that it advances the story so people don't just drool at the pretty animation and stop engaging. Thus putting the "dark arts" in the service of learning. (#3) All three ideas warrant emulation in other contexts! * Find it towards the bottom under the "Making predictions" heading.

vivzkestrel

- A previous comment by me about my list of absolutely gorgeous, interactive, animated, high dynamic learning resources classified as S TIER - S-TIER blogs are those that are animated, visual, interactive and absolutely blow your mind off - A-TIER are highly informative and you ll learn something - opinion blogs at the absolute bottom of the tier list because everyone everywhere ll always have an opinion about everything and my life is too short to be reading all that - these are the S-TIER ones on my system - https://growingswe.com/blog - https://ciechanow.ski/archives/ - https://mlu-explain.github.io/ - https://seeing-theory.brown.edu/index.html#firstPage - https://svg-tutorial.com/ - https://www.lumafield.com/scan-of-the-month/health-wearables - these are the BEST of the BEST, you ll be blown away opening each page is how good they are. i am thinking of creating a bookmark manager that uses my criteria above and runs across every damn blog link ever posted on HN to categorize them as S-TIER, A-TIER, opinion and so on

davispeck

The interactive explanations here are still some of the best examples of how visualization can make ML concepts intuitive. I wish more technical articles took this approach instead of starting with equations.

AlexDunit

Still one of the best explanations of decision trees I've seen. The scroll-driven animation that builds the tree split by split, while simultaneously showing where each data point lands, does in 30 seconds what most textbook diagrams fail to do in three pages

jazzpush2

Amazing. A very cool niche area, dataviz x ai/ml. See also: - mlu-explain.github.io - visxai.io - google PAIR's explorables - GA Tech's poloclub.

anesxvito

Bookmarked.This is exactly the kind of visual reference that's missing from most LLM explainers.You either get a 10,000 word paper or a tweet-length oversimplification. Nothing in between.