A Visual Introduction to Machine Learning (2015)
- AlexDunit - 193 sekunder sedanStill 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
- tonyhschu - 16477 sekunder sedanOne of the creators of R2D3 here. Funny to wake up to this today! Happy to answer questions here or on bsky
- stared - 21593 sekunder sedanIt 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/
- vivzkestrel - 10491 sekunder sedan- 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://ciechanow.ski/archives/
- https://mlu-explain.github.io/
- https://seeing-theory.brown.edu/index.html#firstPage
- 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
- ayhanfuat - 32938 sekunder sedanThis is from 2015. Both technically and conceptually it was ahead of its time.
- smaili__ - 19084 sekunder sedanSo 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.
- davispeck - 6666 sekunder sedanThe 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.
- shardullavekar - 23758 sekunder sedanhas anyone come across an r2d3-style explainer for something as high-dimensional as a Transformer's attention mechanism?
- mvrckhckr - 13900 sekunder sedanThis is still great after more than a decade.
- quickrefio - 17515 sekunder sedanR2D3 did an amazing job here. It’s rare to see statistical learning concepts explained visually this clearly.
- cake-rusk - 30069 sekunder sedanWhere's the rest of it?
- xpe - 11668 sekunder sedanThe 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.
- nullora - 12038 sekunder sedannice
- sp4cec0wb0y - 12157 sekunder sedanDid they not have mobile responsive sites in 2015? Lol
- longtermemory - 30912 sekunder sedan[dead]
- planerde - 26678 sekunder sedan[dead]
- Jhater - 32444 sekunder sedanJosh 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/
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- mileszhang - 16722 sekunder sedan[dead]
Nördnytt! 🤓