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Mathematics for Machine Learning [pdf]

mml-book.com

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Re: Mathematics for Machine Learning [pdf]

#11

Post by random314 »

zer0sugar wrote: post #10
sergeyfilippov wrote: post #8

How would you compare this book to the first part of "Deep Learning" book (by Ian Goodfellow, Yoshua Bengio, and Aaron Courville)? https://www.amazon.com/gp/product/0262035618

I feel obligated to interject here as I have not read the book OP linked to but I have attempted to read the paper weight calling itself a book that you linked to. I have it right here actually. It's basically total trash. They claim to show you how to do the math but at the very best all they do is restate random formulas without any explanation. It's not even good enough to serve as a refresher if you know the math…

As a counterpoint, I have the book and found it to be really helpful.

Re: Mathematics for Machine Learning [pdf]

#12

Post by mkl »

Nicci00 wrote: post #4

Id be useful to have a "math for programmers book" that uses pseudo code instead of math notation. I studied math notation in 8th grade and then forgot about it.

Possibly, but if you want to learn maths, then the notation is one of the smallest, easiest parts of it, and it's really helpful for the bigger, harder parts.

Code is usually way more verbose than maths notation, so things get a lot bigger and it can be a lot harder to see what's going on. Learning maths notation is like learning the basic syntax of a programming language related to one you know already - there's not much to it and it doesn't take long to be able to read it comfortably. If you can already code then you know the basics and many relevant concepts already.

Re: Mathematics for Machine Learning [pdf]

#13

Post by Impossible »

Nicci00 wrote: post #4

Id be useful to have a "math for programmers book" that uses pseudo code instead of math notation. I studied math notation in 8th grade and then forgot about it.

A Programmer's Introduction to Mathematics is probably what you're looking for. https://pimbook.org/

Re: Mathematics for Machine Learning [pdf]

#15

Post by ivansavz »

Nicci00 wrote: post #4

Id be useful to have a "math for programmers book" that uses pseudo code instead of math notation. I studied math notation in 8th grade and then forgot about it.

Check out this short excerpt of definitions and examples of the math "alien symbols": https://minireference.com/static/excerpts/set_notation.pdf They are really not that bad once you learn their meaning + very useful shorthand (you can think of math notation as a DSL with specific expressions for math operations).

Longer preview of the book: https://minireference.com/static/excerpts/noBSguide_v5_previ... and here is another preview of the LA book: https://minireference.com/static/excerpts/noBSguide2LA_previ... Both books have been pretty popular with the programming crowd. They use standard math notation, but there are lots of code examples and computing analogies, so you'll feel right at home.

Re: Mathematics for Machine Learning [pdf]

#16

Post by ah700 »

Impossible wrote: post #13
Nicci00 wrote: post #4

Id be useful to have a "math for programmers book" that uses pseudo code instead of math notation. I studied math notation in 8th grade and then forgot about it.

A Programmer's Introduction to Mathematics is probably what you're looking for. https://pimbook.org/

I bought the book attempted to study from it and I am not a fan. It covers topics too briefly to be called an "introduction" to mathematics. If you have a solid math background and need a refresher you may find it useful, otherwise I found MIT OCW Mathematics for Computer Science to be a much more suitable introduction, and it comes with problem sets and answers (for the 2010 course). You can also purchase the course notes in book form on Amazon.

https://ocw.mit.edu/courses/electrical-engineering-and-compu...

solutions https://drive.google.com/drive/folders/0B4G5KBKimr07WXRlT0VK...

physical book https://www.amazon.com/Mathematics-Computer-Science-Eric-Leh...

Re: Mathematics for Machine Learning [pdf]

#17

Post by disgruntledphd2 »

random314 wrote: post #11
zer0sugar wrote: post #10

Earlier quoted context omitted.

I feel obligated to interject here as I have not read the book OP linked to but I have attempted to read the paper weight calling itself a book that you linked to. I have it right here actually. It's basically total trash. They claim to show you how to do the math but at the very best all they do is restate random formulas without any explanation. It's not even good enough to serve as a refresher if you know the math…

As a counterpoint, I have the book and found it to be really helpful.

I enjoyed the book, but have a background in this area.

I was amused by the suggestion that computer science undergrads could handle the book, as clearly the authors and I have met very different computer science undergrads.

Re: Mathematics for Machine Learning [pdf]

#18

Post by mlthoughts2018 »

disgruntledphd2 wrote: post #17
random314 wrote: post #11

Earlier quoted context omitted.

As a counterpoint, I have the book and found it to be really helpful.

I enjoyed the book, but have a background in this area. I was amused by the suggestion that computer science undergrads could handle the book, as clearly the authors and I have met very different computer science undergrads.

The Courville, Goodfellow and Bengio book is definitely suitable for undergraduates. In my current job, we often have new junior level (bachelor’s grads) ML hires work through that book and present chapters in the team reading group. In my experience both as a TA in my PhD program and in industry, that book is fairly easy to read through for anyone with solid understanding of linear algebra and vector calculus, which are freshman / sophomore level college math courses.

Re: Mathematics for Machine Learning [pdf]

#19

Post by sn9 »

uwuhn wrote: post #7
TallGuyShort wrote: post #6

Earlier quoted context omitted.

"Coding the matrix" was the breakthrough for me in grokking linear algebra, and this is what it does. Things are explained in terms of matrices and the mathematical transformations, and then explained in terms of python data structures and a loop over the elements. And most of the examples are computer science, like rotating images.

I remember this course when it first came out, but didn't go through it since I didn't actually know how to program/code back then. Should I just buy the paperback off Amazon?

It's pretty cheap. I'd say go for it.

Re: Mathematics for Machine Learning [pdf]

#20

Post by zer0sugar »

mlthoughts2018 wrote: post #18
disgruntledphd2 wrote: post #17

Earlier quoted context omitted.

I enjoyed the book, but have a background in this area. I was amused by the suggestion that computer science undergrads could handle the book, as clearly the authors and I have met very different computer science undergrads.

The Courville, Goodfellow and Bengio book is definitely suitable for undergraduates. In my current job, we often have new junior level (bachelor’s grads) ML hires work through that book and present chapters in the team reading group. In my experience both as a TA in my PhD program and in industry, that book is fairly easy to read through for anyone with solid understanding of linear algebra and vector calculus, which…

Here's a photo of a random page.

https://i.imgur.com/vv1CRLv.jpg

You can trust me when I say the entire book is about as unreadable as that and often worse. I'm not afraid of math either. But the book certainly is not teaching anyone anything.

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