Mathematics for Machine Learning Perfect Paperback – 1 January 2021

Book printing and pages are thick & best quality.

* Nicely packed* High quality page* Excellent printing

I've used the online copy of this book when going through the Math for ML specialisation in Coursera. It's pretty comprehensive in handling the core areas of Math required for ML. I'd also recommend it as a quick refresher in Math if you're preparing for ML/DS interviews. Had to get the physical copy, because it's much easier to navigate, and unlike other tech books this one is not to be obsolete anytime soon.

Good Book for ML to understand its mathematics. If you are not good at mathematics but learn to work in ML then at least you can use this book. For theories and coding many books and internet website available.You can also download freely this book from author website.

This is best but Page printout colourless (Black and white)

Recommend

It looks like it has been printed locally, images are black and white rather it should be coloured.

Livro que inter-relaciona conhecimentos de Matemática e de Computação, complementando assuntos básicos de ambas as disciplinas.

This is it. I got pretty far with this book in my graduate studies. The covered math is all you need to have a solid foundation to read cutting-edge papers and develop advanced intelligent systems. There are also plenty of exercises to consolidate your knowledge. Well done to the authors.

I had been looking for a book to bridge the gap between implementing machine learning code on the granular level and understanding it from a theoretical perspective and the search wasn't going well. Lots of other books that I tried before finding this one promised to help programmers become better mathematicians (or at least show them the math they need to learn in order to achieve that goal) but would almost always just provide code without context, or run through some incredibly basic, introductory level math without explaining at all how it connects to the various machine learning algorithms you'll be implementing as a programmer.This book, however, takes the math seriously, and is incredibly direct and efficient in the introduction of new, relevant topics in calculus, linear algebra, and probability and statistics that you'll need to know if you want to truly understand the libraries you're using. I find myself reading a section in the book, going back to a "dedicated" textbook on the subject at hand - linear algebra or calculus or probability and statistics - and further studying the material, and then going back to Mathematics for Machine Learning to make sure I understand the topic better. This is the exact learning flow that I wanted, and the book delivers. Can't recommend enough!

Este libro sirve como guía o compendio de temas matemáticos que se utilizan en Machine Learning. Es recomendable tener nociones de Álgebra Lineal, Cálculo de varias variables y Estadística para poder leerlo.¿Para quién es este libro? Para aquellos que ya han llevado cursos de las materias antes mencionadas y necesitan saber como aplicar esos conocimientos al Machine Learning.¿Para quién no es este libro?Para quienes apenas se están iniciando en el aprendizaje de las matemáticas superiores. Si buscas un libro introductorio a las matemáticas necesarias para Machine Leaening, no es para tí. En su lugar recomiendo libros como "Linear Algebra" de Friedberg y "Cálculo Avanzado" de Fulks.A mi en lo personal me gustó mucho el libro.Recomiendo buscar el libro en internet (se encuentra gratuito en pdf) y revisarlo, antes de comprarlo. A pesar de tenerlo en PDF, me es más comodo leerlo en físico que en digital.

Wide ranging with basic principles of foundation in maths and machine learning