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by dafrdman 2119 days ago
I'm linking to a free online book I just finished called Machine Learning from Scratch. The book aims to cover the complete, technical, "under the hood" details that other ML textbooks don't. To do that, it shows all the mathematical steps to derive common algorithms and demonstrates how to fit each one from scratch in Python (using just numpy).

You might like this book if you are interested in ML and like to really understand what's going on behind the algorithms. Personally, when learning about these algorithms I would understand them intuitively but not feel comfortable constructing them myself. Even if you totally grasp the algorithms, seeing them derived from scratch is a great way to better understand the comparative advantages between competing models.

The code and math are pretty simple, so there should be a low barrier to entry.

I'm hoping to make the book somewhat of a breathing document, so if you have any edits, questions, or suggestions, I'm all ears. You can reach me at dafrdman@gmail.com. Thanks a lot!
2 comments
stevesimmons 2119 days ago
Nice work!

Can we flag edits on github somewhere?

I found a typo at line 60 of https://dafriedman97.github.io/mlbook/content/conventions_no..., where your second "is written as $$" is missing the empty line before the "$$".

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dafrdman 2119 days ago
Thanks for the catch! Ugh those pesky $$s. Changed it now.

Looks like you found the repository. Do you think it would be enough to raise an issue there? (at https://github.com/dafriedman97/mlbook)? I'll look into linking directly from the book to the repo.

Thanks!

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stevesimmons 2119 days ago
Added the issue.

Yes, I did find the repo. Hesitated adding the issue right away because the source files have ".md.txt" and ".html", but not the original ".md" files for me to fix them directly.

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dafrdman 2119 days ago
Yeah the book was built with JupyterBook. It's an awesome tool but I lose track of what it does to the .md files when creating the website.
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Bedon292 2119 days ago
You said in other comments that you used JupyterBook to make it. Would you consider open sourcing that so that others can contribute?
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