Math for Programmers: 3D Graphics, Machine Learning, and Simulations with Python

This book is awesome! It even comes with a free eBook which is included inside (After the Mathematical Notation Reference Page). The book goes in depth about how it came to be written and the author talks about his life in his company. In there you are provided with examples, figures, exercises with solutions that are explained very very well. I've had the book for a couple of months now, while being a full time student and I still have not gone through the entire book (I have read it through fully but haven't gotten around to study it) I have learned very good tips and tricks from the book which helped me a lot in my CS classes and sometimes I would even surprise my professors and I recommended this book to many of my classmates (only 2 of them got it and they loved it), in general this is a very good resource to get your through CS and become someone that you want to be. (remember you need to be a little experienced with programming and math in order to understand this book). Good luck to everyone!

Explained the math with useful code which helped to understand the underlying ideas.

I'm constantly on the lookout for new resources to share with my teams, which tend to be composed of folks from all kinds of backgrounds: formal CS, self-taught, code-camps, and other educational backgrounds (or even fields). Not everyone has the same level of math skills at the start, and some need refreshers from time to time.I had a chance to review Paul Orland's book and compare it to some other books on my shelf. This book doesn't try to be a rigorous first principles math book. It doesn't focus on trying to give you a deep dive on the math topics (e.g. looking at proofs and the like). It also isn't a book geared towards Computer Science specifically (no math topics on sets, logic, graph theory, complexity, combinatorics, etc).instead, it covers a selection of topics of interest to programmers/developers, delivered in three parts/areas: 1) 2/3D math (particular linear algebra techniques for doing various matrix calculations), but then applying to higher dimensions, 2) Basic Calculus techniques for simple physical simulation and Fourier analysis, and 3) a light intro into some useful techniques frequently found in Machine Learning applications.What I like is that is focuses on explaining enough of these math topics you can get the gist, and more importantly, how to think about these technique and translate to programming (in Python, here). After reading it, I took away an appreciation of how to apply some new (old) tools to practical problems at hand (e.g. fitting functions to data, basic classifiers, etc)For my team mates who have very little math background, they may need a little help, and online resources (like Khan Academy) are good supplements. This is not "dumbed down" content, it still takes some study. It is approachable though.For folks who remember their geometry, algebra, trig, and basic calc, but haven't really had to apply it to programming, this will be informative on how to think about certain kinds of problems and implement certain algorithms in the event that what they are looking for isn't immediately found in the language of choice's math or other libraries.Overall, a worthwhile read if you want to refresh on math as a developer.

I found this book to have really excellent coverage of a number of important topics in math. Often programmers, even ones with a lot of experience, have become a little distanced from the kinds of math which drives a lot of modern tech - computer graphics, optimization, machine learning etc. A decent appreciation for the math underpinning these can open a LOT of doors for those who've become a little stuck with more dull or mundane programming tasks, but the problem is how to acquire (or refresh) these skills. Math courses online can cover the ground eventually, but there are a lot of areas to know about and finding the right relevance or level of detail is hard. The author of this book really hit the mark for me, and the fact that every concept is illustrated in code makes the knowledge transfer significantly easier. Some of the stuff was definitely stuff I knew but had forgotten or hadn't used in a while (matrices, dot and cross products, calculus), other was familiar but I'd never applied it (Fourier series), and some was completely new. The book doesn't pretend to give an encyclopedic coverage of math, neither does it make claims about depth for the concepts it does cover, but it DOES give more than enough to get you right into the subject with a minimum of effort and in a really engaging way.Regarding programming knowledge, I think you do need some to get the most of it, though it doesn't need to be in Python - the book is for programmers after all.I'd thoroughly recommend it.

This book provides a fantastic grounding for developers/programmers who are building systems, large and small for business as well as pleasure. The Mathematics topics here serve developers well because as the new AI / ML wave broadens out, it will be critical to have a firm grounding in topics closely related to Linear Algebra and matrices. This book tackles a rarely discussed area of upskilling for the modern developer and this book is vital for the community to have access to. I give it a very strong endorsement and buy rating. Even if you are NOT a python developer, get it for explanations and to see the implementations of its ideas.

Great step-by-step introduction/refresher to applied mathematics, with common software engineering problems in mind.If you already have a good background in mathematics, you won’t learn much.But for all the software engineers with low maths background (if any), this guides you through practical problems. building a better understanding of the concepts... with real use-cases.I wish it existed a few years ago, I would have recommended it to many teammates

Me enseño lo que nadie pudo en mi vida estudiantil. Explicar el por que se usan las cosas y en que contexto.

Eines der besten Bücher die ich kenne um höhere Mathematik zu lernen. Aber Achtung: das Buch ist anspruchsvoll und man muss bereit sein ziemlich Zeit zu investieren. Was das Lesen erleichtert ist wenn man bereits ein guter Phyton Programmierer ist.Der Author ist aber ein ausgezeichneter Ditakt.

A good book which I enjoyed reading and working through the examples with GCSE students in the top maths group.One small complaint - the printed book comes with a free ebook which is in black and white. I have also seen the same ebook in colour, which is much much better. I guess the colour one is if you pay the enormous cost for the ebook instead of just the free version.Do not buy the ebook unless you get the full colour version.Do not buy this book if you know maths at A-level or beyond.Otherwise, this is a really good and well written book that makes complex problems simple through computing examples.

Good book in excellent condition, very happy with product.

It is a very nice book, to enjoy of reading. It would be better with color images asin the pdf book.