[HN Gopher] A Visual Introduction to Machine Learning (2015)
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A Visual Introduction to Machine Learning (2015)
Author : vismit2000
Score : 301 points
Date : 2026-03-15 10:47 UTC (12 hours ago)
(HTM) web link (r2d3.us)
(TXT) w3m dump (r2d3.us)
| ayhanfuat wrote:
| This is from 2015. Both technically and conceptually it was ahead
| of its time.
| mdp2021 wrote:
| It's a pity there seems not to be new (or other) material from
| Tony Hschu and Stephanie Jyee.
|
| (Or can anybody find something more?)
| Jhater wrote:
| 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 wrote:
| Where's the rest of it?
| jojohack wrote:
| Part 2: https://r2d3.us/visual-intro-to-machine-learning-
| part-2/
| shardullavekar wrote:
| has anyone come across an r2d3-style explainer for something as
| high-dimensional as a Transformer's attention mechanism?
| lamename wrote:
| Not quite, but these help
|
| https://poloclub.github.io/transformer-explainer/
|
| https://youtu.be/wjZofJX0v4M?si=gT8Zlz1IY14KV_ju
| stared wrote:
| 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/
| kengoa wrote:
| Nice list! I remember HN talking about
| https://students.brown.edu/seeing-theory/ when it came out but
| sadly it seems like this website was discomissioned.
|
| Added an entry for my data visualisation tool here:
| https://github.com/stared/interactive-machine-learning-
| list/....
|
| Edit: found an updated link for seeing theory so I fixed it in
| the PR above. Feel free to cherry-pick if #24 is not relevant.
| smaili__ wrote:
| 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 wrote:
| R2D3 did an amazing job here. It's rare to see statistical
| learning concepts explained visually this clearly.
| tonyhschu wrote:
| One of the creators of R2D3 here. Funny to wake up to this today!
| Happy to answer questions here or on bsky
| reader9274 wrote:
| Any plans for more articles, 10 years later?
| Genbox wrote:
| If I would like to build a visualization like this, but for a
| data ingestion pipeline, any tips on where to start?
|
| I have it visually in my head, but it feels overwhelming
| getting it into a website.
| tonyhschu wrote:
| Sort of like this?
| https://docs.tecton.ai/docs/introduction/interactive-tour I
| used https://github.com/xyflow/xyflow for this, with css
| animations for the edges. It's probably easier now with
| coding agents and what not
| avabuildsdata wrote:
| fwiw I work on data ingestion pipelines and I've found that
| starting with just boxes-and-arrows in something like
| Excalidraw gets you 80% of the way to knowing what you
| actually want. The gap between "I can picture it" and "I can
| build it on a webpage" is mostly a d3 learning curve problem,
| not a design problem.
|
| xyflow that the creator mentioned is probably the right call
| for pipeline DAGs though -- we use it internally for
| visualizing our scraping workflows and it was surprisingly
| painless to get running
| mvrckhckr wrote:
| This is still great after more than a decade.
| sp4cec0wb0y wrote:
| Did they not have mobile responsive sites in 2015? Lol
| 1wheel wrote:
| 2015 was about the last year you could get away with publishing
| an interactive graphic with a fixed width -- this made it
| harder do really creative/original work.
| nullora wrote:
| nice
| xpe wrote:
| 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 wrote:
| - 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
| 1wheel wrote:
| https://visxai.io/ has a bunch more too -- see the Hall of Fame
| section at the bottom for some of the highlights.
|
| I also made a dozen of these a couple years ago, my two
| favorites:
|
| - https://pair.withgoogle.com/explorables/fill-in-the-blank/
|
| - https://pair.withgoogle.com/explorables/grokking/
| davispeck wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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.
| 3abiton wrote:
| 3blue1brown has amazing content. Actually he had his own visual
| language.
| anesxvito wrote:
| Haven't come across his stuff yet, will check it out. Got any
| specific videos you'd recommend starting with?
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