Machine Learning: Step-by-Step Guide To Implement Machine Learning Algorithms with Python

by Rudolph Russell

This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a theoretical and a practical way, and we'll implement many machine-learning algorithms using the Scikit-learn library in the Python programming language. In the first chapter, you'll learn the most important concepts of machine learning, and, in the next chapter, you'll work mainly with the classification. In the last chapter you'll learn how to train your model. I assume that you've knowledge of the basics of programming
This book contains illustrations and step-by-step explanations with bullet points and exercises for easy and enjoyable learning.

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106 pages, Paperback

Published May 22, 2018

Reviews

[Azra Tuni · Rating 1 out of 5]

I started reading this book with one clear objective in mind, that is, even if I don't learn more algorithms, I absolutely will learn Linear Regression from this book which is like the most basic algorithm. I had thought this book to be more beginner-friendly... This book does have a section for Linear Regression (what I was looking forward to) along with other algorithms and stuff but I didn't get it. I read the LR section multiple times and just didn't get it.

NB: I do have programming knowledge which is the pre req of this book.