Bradley Peter. Machine Learning: A Comprehensive, Step-by-Step Guide to Intermediate Concepts and Techniques in Machine Learning

Independently published, 2018. — 79 p.Do you want to impress the processes that you are working on? Do you want to make your machines more intelligent? If your answer to any of those questions is yes, then you have come to the right place.This book is a sequel to the book titled 'Machine Learning: A Step-by-Step guide.' In the first book, you gathered information on what machine learning is, and the different algorithms that one needs to know. This book is written for those who have a basic understanding of what machine learning is.In this book, you will gather information on:
Practical examples of machine learning
How to build a machine learning algorithm in Python
An introduction to deep learning and neural networks
How to create a neural network in Python using KerasPractical Examples of Machine Learning
Advantages and Disadvantages of Machine Learning
How to Create and Train Machine Learning Models
An Introduction to Deep Learning
An Introduction to Neural Networks
Building Your First Algorithm in Python
How To Build An Algorithm in Python
How To Evaluate Machine Learning Algorithms in Python?
How to Develop a Neural Network in Python using KerasSources