dafrdman

6 ms·

1. 1.▲
   by dafrdman 6y ago

   You can now find a pdf version of the book at https://github.com/dafriedman97/mlbook/blob/master/book.pdf . JupyterBook is still working on the PDF creation, so this doesn't have any of the images un
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   by dafrdman 6y ago

   Thanks so much! I would say two major differences: 1, as you mention, it codes each method up from scratch in Python readers can really see each step the method uses. 2, it is focused on the derivations of these methods, rather than their i
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   by dafrdman 6y ago

   It's definitely not deep learning focused. I wanted to start by introducing the models machine learning practitioners should all know. But collaborative filtering and stuff along those lines would be a good addition! Thanks for the fee
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   by dafrdman 6y ago

   My hesitance with "Application" is that sounds like I'm going to use some interesting dataset or do some cool project (and this is essentially using iris to build basic models). How about "code" becomes "implem
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   by dafrdman 6y ago

   That's sensible. Maybe change construction to code and code to application? Or keep construction but rename code? I'll have to brainstorm. I definitely don't want people missing the construction section so this is great feedb
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   by dafrdman 6y ago

   I definitely agree. I should add more comments explaining what things like .T does--it's not that it's hard to grasp, but it might turn away newbies. Thanks for the suggestion! Pandas is only used in the "code" sections,
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   by dafrdman 6y ago

   Agreed. That's #1 on my list right now.
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   by dafrdman 6y ago

   I agree though I saw that as outside the scope of this book. I tried to be clear in the introduction that the book is a "user manual" of sorts that simply shows how to construct models, rather than how to decide between them, what
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   by dafrdman 6y ago

   Perhaps I should have been clearer, but the "code" section within each chapter is not "from scratch". The "construction" section is "from scratch" in that it only uses numpy (not scikit learn). The sc
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    by dafrdman 6y ago

    Good question. I definitely prefer downloadable books myself. I made it in JupyterBook because that was easiest with the executable ipynb files. I'll look into whether I can make it downloadable and update you if so.
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    by dafrdman 6y ago

    Good ideas. I think I'll try to add an appendix, minimize the number of numpy functions used, and explain any of the weird ones that are real time savers. Thanks for all your thought.
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    by dafrdman 6y ago

    I hadn't even considered licensing it. Want to email me and we can talk? My email is dafrdman@gmail.com. That said, you're welcome to use it (though my lawyer father suggests I say that this "verbal contract" is revocabl
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    by dafrdman 6y 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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    by dafrdman 6y ago

    Thanks for the feedback. Sounds like you're not alone in your thoughts on numpy. I'll brainstorm better solutions--maybe explaining each numpy function in a side note or adding a numpy overview to the appendix. It just makes thing
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    by dafrdman 6y 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
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    by dafrdman 6y ago

    Thanks so much for your feedback. Definitely open to comments! I agree 100% that any use of packages can be intimidating for newbies. I experimented at first with creating the models without using numpy and I thought that it actually made i
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    by dafrdman 6y ago

    Thanks for the helpful feedback. I wanted to put emphasis on the graphs so I chose to hide the code but maybe it's not worth the cuteness of the "click to show". Changing that now.
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    by dafrdman 6y ago

    Good call! I'll work on that ASAP
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    by dafrdman 6y ago

    The approach to this book is very similar to nnfs.io (a similar focus on deriving models from the bare bones). The biggest difference is that his focuses on deep learning while mine covers a) a wider range of models and b) more introductory
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    Show HN: ML From Scratch – free online textbook(dafriedman97.github.io)

    259 points by dafrdman 6y ago|54 comments
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    by dafrdman 6y 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