With so many books on Python machine learning, making a choice is becoming increasingly difficult. You’re investing both your time and money to learn something that can open new career paths for ...

For example, I think that one "introduction to machine learning" book should really be enough, there's no point in reading multiple "introductions to ML," unless you really feel like that the ...

Machine Learning: A Practitioner’s Approach. The book is authored by Vinod Chandra and Anand Hareendran S. The book’s target demography is largely the aspiring computer science engineering graduates.

Books give you an overview of theory, but it’s also important to implement and play with some practical machine learning systems. Udacity and Coursera usually have high quality courses with ...

I don’t expect a book on machine learning to extensively cover deep learning, but in Hands-on Machine Learning, Geron has managed to pack a lot in 400 pages.You start with a great history of ...

Mastering machine learning is not easy, even if you’re a crack programmer. First, as the name suggests, machine learning is software that learns by itself as opposed to being instructed on every ...

This book explains what it covers very well, but in a field that's moving as fast as big data and machine learning, its sound but rather traditional approach may soon look a little dated.

Based on a tip from a reader, we checked 18 of the 46 citations in the book {Mastering Machine Learning: From Basics to Advanced}. Two-thirds of them either did not exist or had substantial errors….