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I really recommend this explorable explanation: https://setosa.io/ev/ordinary-least-squares-regression/ https://setosa.io/ev/ordinary-least-squares-regression/

by stared 1y ago

I really recommend this explorable explanation: https://setosa.io/ev/ordinary-least-squares-regression/ https://setosa.io/ev/ordinary-least-squares-regression/ And for actual gradient descent code, here is an older example of mine in PyTorch: https://github.com/stared/thinking-in-tensors-writing-in-pytorch/blob/master/3%20Linear%20regression.ipynb https://github.com/stared/thinking-in-tensors-writing-in-pyt...

revskill 1y ago
Google search is evil by not giving me those resources.
- sorcerer-mar 1y ago
  This is an all-time great blog post for this line alone: "That's why we have statistics: to make us unsure about things." The interactive visualizations are a great bonus though!
- mhb 1y ago
  Kagi FTW?
  - billbrown 1y ago
    That was my initial thought, too. But I didn't know what the original Google search consisted of and the site didn't show up in a couple Kagi searches I tried. (Aside from the obvious titular one, of course.)
- stared 1y ago
  Yeah - I wanted to post it here, but after searching for "linear regression explorable explanation" I got some other random links. Thankfully, I saved the PyTorch materials + https://pinboard.in/u:pmigdal/t:explorable-explanation https://pinboard.in/u:pmigdal/t:explorable-explanation.
- Nifty3929 1y ago
  Google does however provide this very nice course that explains these things in more detail: https://developers.google.com/machine-learning/crash-course https://developers.google.com/machine-learning/crash-course