Pen and Paper Exercises in Machine Learning (2022)

Seems to be cool, but, one of thing that most annoys me on studying machine learning is that I may dive as deep as it is possible in theory, but I can&#x27;t see how it connects to the practice, i. e. how it makes me choose the correct number of neurons in a layer, how many layers, the activation functions, if I should use a neural network or other techniques, and so on...<p>If someone have something explaining that I&#x27;ll be grateful

Very neat! Reminds me of Tom Yeh&#x27;s &quot;AI By Hand&quot; exercises [0].<p>[0] <a href="https:&#x2F;&#x2F;www.byhand.ai&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.byhand.ai&#x2F;</a>

Looks neat! My only criticism would be that the solutions are given right after the questions so I couldn&#x27;t help to read the answer of one question before thinking it through by myself.

This is really neat! I work in machine learning but still feel imposter syndrome with my foundations with math (specifically linear algebra and matrix&#x2F;tensor operations). Does anyone have any more good resources for problem sets with an emphasis on deep learning foundational skills? I find I learn best if I do a bit of hands-on work every day (and if I can learn things from multiple teachers’ perspectives)

So who among current ML practitioners building “useful” ML could solve some of these?<p>_Should they_ be able to?

complete with solutions, beautiful, thank you for sharing!<p>I&#x27;d be interested in more of these pen and paper exercises, if there is such a term, for other topics.

Discussed at the time:<p><i>Pen and paper exercises in machine learning (2021)</i> - <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=31913057">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=31913057</a> - June 2022 (55 comments)

Funny how mathematicians always try to sneak their linear algebra and matrix theory into ML. If you didn&#x27;t know any better, you&#x27;d think academicians had invented LLMs and are the experts to be consulted with.<p>If anything academicians and theoreticians held ML back and forced generations of grad students doing symbolic proofs, like in this example, just because computational techniques were too lowbrow for them.

Isn&#x27;t arxiv meant for research level papers? Surprised to see this hosted there.

Love it.

If someone could turn these into an adaptive Khan Academy style app, that would be incredible