Some of the best educational/visualization tools I've seen for learning data science. I prioritize quality over quantity so will only post the best of the best that I find here.
The resources below are selected by the following criteria:
- Explained in simple language while still explaining the math without dumbing it down.
- Usually the have some kind of animation or interactive component.
- The visual concepts are presented clearly and unambiguously.
- Setosa - https://setosa.io/#/
- Distill.pub - https://distill.pub -
- http://worrydream.com/ExplorableExplanations/
- https://distill.pub/2020/communicating-with-interactive-articles/
- MLU Explainer - https://mlu-explain.github.io
- UMAP / T-SNE / PCA Visualizer - https://projector.tensorflow.org
- R2 D3 Machine Learning Explainers - http://www.r2d3.us
- Backpropagation Explainer - https://xnought.github.io/backprop-explainer/
- Tensorspace.js - Neural Network 3D Visualization - https://github.com/tensorspace-team/tensorspace
- Matrix Multiplication Visualizer http://matrixmultiplication.xyz
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Seeing Theory - https://seeing-theory.brown.edu
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A visual explanation of Permutation Testing - https://www.jwilber.me/permutationtest/ -
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Algorithms Step by Step Visualizer - https://www.hackerearth.com/practice/algorithms/sorting/bubble-sort/visualize/ - This page starts on bubble sort, but there is a highly navigatable menu on the left side with a ton of algorithms on the side.
- Steven Witten Incredible 3D designer and blogger - https://acko.net
- Bret Victor
- Mingwei Li - https://tiga1231.github.io
- D3 Basic guide - Yan Holtz - https://www.d3-graph-gallery.com/index.html
- 3 Blue 1 Brown -
- Zach Star
- Statquest
- Brilliant.org
- Datacamp.com
- Khan Academy
- https://mathigon.org