tonyhschu

5 ms·

1.
by tonyhschu 6mo ago
Very cool. I do something like this but with Playwright. It used to be a real token hog though, and got expensive fast. So much so that I built a wrapper to dump results to disk first then let the agent query instead. https://uis
2.
by tonyhschu 6mo ago
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
3.
by tonyhschu 6mo ago
One of the creators of R2D3 here. Funny to wake up to this today! Happy to answer questions here or on bsky
4.
by tonyhschu 1y ago
That workflow sounds amazing. How do you set that up? Got any code for it that we can look at?
5.
by tonyhschu 5y ago
Yeah! This was done before CSS scroll-snap is a thing. I'd probably use scroll snap now. See: https://developer.mozilla.org/en-US/docs/Web/CSS/CSS_Scroll_...
6.
by tonyhschu 5y ago
Second this. Idyll is the closest thing I know that makes this sort of thing approachable. Those dot animations are unfortunately very custom.
7.
by tonyhschu 5y ago
Funny to see this on the homepage today. Part 1 was done so long ago now that looking back on that code is equal parts intimidating and embarrassing. Maybe this is the motivation I need to actually fix that stupid feet/meter thing.
8.
Making sense of COVID19 through interactive simulations(r2d3.us)
3 points by tonyhschu 6y ago|0 comments
9.
by tonyhschu 8y ago
Author here – Part 2 uses: - React for DOM rendering - D3 for visualization geometry - RxJS for handling state (i.e. turning scroll position into animated properties) - PIXI for WebGL bits (i.e. all the little circles moving around)
10.
by tonyhschu 11y ago
The decision tree model was generated from http://scikit-learn.org in Python. The JS is a complete mess, but I'll try to write up how it works in the next couple days.
11.
by tonyhschu 11y ago
Thanks Brandon! We're certainly thinking about it. We'll work out way up there.
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by tonyhschu 11y ago
OP here. What kinds of sources are you looking for? We built this based on some of the lectures in Stanford's statistical learning class ( http://online.stanford.edu/course/statistical-learning-winte... ) as well as
13.
by tonyhschu 11y ago
Thanks! Yeah absolutely. We are working our way up to those. Our tentative plan is to tackle bias-variance trade-off next, then random forests, then neural networks.
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Show HN: Intro to Machine Learning in Interactive D3.js Visualizations(r2d3.us)
128 points by tonyhschu 11y ago|12 comments