Independently Published Machine Learning For Absolute Beginners: A Plain English Introduction

Easy to understand as a novice and loved the fact that in the last couple of chapters, you actually get to put the book to use by building and optimising a decision tree based machine learning model using Python.

I highly recommend this book for people who want to start with Machine learning. It is a great starting point's book to get into this world. Concepts are very we'll explained. I started to understand things I had not been able to understand with other books and YouTube videos. It is helping me a lot to understand the foundations and key concepts of Machine learning.

I bought this book for my wife and I have never seen her so happy! She rarely finishes an academic book, but this one felt so natural for her to get to the end of it. She had no knowledge of machine learning but a physics background. This book gives a great way of starting into this fascinating topic!

An excellent book for beginners which explains machine learning terminology and concepts quickly. Great when you need a grasp of the basics quickly

Very logically structured and with clear chapters which hang together (about 5-10 pages long). It covers the components/decisions to make in Machine learning, data preparation, the main algorithm methods, the development environment and making a model in python. Don't be put off by the python you can read 90% of the book not knowing anything about Python. Great value for money I do have a background in stats and algorithms so even though the language is clear some of the underlying concepts do take a bit of thinking about. A suggestion if you cannot take the algorithms on board is to get 20 pictures of dinosaurs and try putting them into 2 categories using each of the "unsupervised" algorithms that the author describes - for the supervised algorithms get 20 pictures of cats/dogs and correctly label half of them (the "training set") as "Cat" or "Dog" leaving the other half without labels (to use either as "test" data or "actual" data)...