ML From Scratch
Learning and science
machine learning textbook
SHOW HN2020
How HN took it
6 positive, 14 neutral or asking, 0 mixed, 4 critical, out of 24 comments about the project. Thread score +0.01.
Idea: 4 for, 1 againstDocs: 2 for, 1 againstDesign: 0 for, 1 againstExecution: 0 for, 1 against
The thread, comment by comment
Each row is a top-level comment and its replies, in HN's order. Select a cell to open that comment on HN.
positive neutral or mixed critical about another commenter or something else the maker
What HN said
What people liked
Good for readers who want to understand algorithms mathematically
From 2 comments
I have a different view :) I feel this book is the ideal companion for intermediate to advanced Python developers/data scientists. People who know pandas pretty well, and so are…
stevesimmons on HNGreat resource! I’ve been looking for something with complete derivations all in one place. I've been looking for a while but haven't been able to find something like this.…
christinahope on HN
Well-commented and rigorous presentation
From 1 comment
I have a different view :) I feel this book is the ideal companion for intermediate to advanced Python developers/data scientists. People who know pandas pretty well, and so are…
stevesimmons on HN
Objections
Relies on numpy, which can obscure how things work for beginners
From 2 comments
Excellent! Very kind of you to do this. Are you accepting comments? If not, ignore the following. :) As someone who learned how to program from trial and error via tutorials on…
fartcannon on HNI wholeheartedly agree with this. As a software developer without a strong math education, any time I open a "from scratch" ml learning resource, I immediately close it because I…
infinitybeyond on HN
Calling it from scratch is misleading since scikit-learn is used in code sections
From 1 comment
That's a really cool initiative, but I think we disagree on the term "from scratch". Taking a look at the source code, I see you're using sklearn - which is a great tool - but,…
atum47 on HN
Notation and some numpy functions are hard to follow
From 2 comments
Thanks for the summary, the object oriented stuff is fine in my mind. The trouble with the code comes from things like the numpy functions. I have experience in matrices for…
Cieric on HNThe 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…
dafrdman on HN
Requests
Add SVMs
From 1 comment
Looking through the topics, a useful addition would be SVMs.
bonoboTP on HN
Downloadable epub or pdf version
From 1 comment
This looks fantastic! As a bit of a selfish question, have you considered also offering a downloadable epub of this book? I've been trying to keep my long-form digital reading to…
shadowoflight on HN
Export raw code separate from notebooks
From 1 comment
Just did a quick scan and looks pretty good! Would it be possible to add an option for exporting the raw code (maybe broken down by chapter/section) separate from the notebooks?…
sgron on HN
Add a numpy appendix or more explanatory comments
From 2 comments
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…
dafrdman on HNI think there is a balance to be struck. You should totally use numpy for the arrays and basic math applications. But say on the first example you use `self.X.T` what does `.T`…
Bedon292 on HN
Questions
Is the project open sourced and can it be licensed for company use?
From 2 comments
You said in other comments that you used JupyterBook to make it. Would you consider open sourcing that so that others can contribute?
Bedon292 on HNI'd love to include the book to our company internal learning resources. Can you include an official license by any chance? Thank you
ohuhu on HN
How does it compare to Introduction to Statistical Learning or Elements of Statistical Learning?
From 1 comment
This book is awesome! How does this compare to Introduction to Statistical Learning or Elements of Statistical Learning? Other than the addition of code?
beccaaf1229 on HN
Alternatives named
nnfs.io (Neural Networks from Scratch)
From 1 comment
First thing I thought of when I read the title was sentdex's nnfs.io (neural networks from scratch.) I don't have time to look at this in full right now, are there any major…
Cieric on HN
Elements of Statistical Learning
From 1 comment
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…
dafrdman on HN
fast.ai course
From 1 comment
I agree with you in theory. I really hate that the fast.ai course uses their own fast.ai library. Numpy is a bit different though as it “fixes” inefficiencies in Python’s typing…
ABeeSea on HN