Machine Learning: A Comprehensive, Step-by-Step Guide to Learning and Understanding Machine Learning Concepts, Technology and Principles for Beginners: 1

© Copyright 2018 Peter Bradley All rights reserved.

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Table of Contents

Introduction

Chapter One: What is Machine Learning?

Chapter Two: Facts about Machine Learning

Chapter Three: Types of Machine Learning

Chapter Four: Top Six Real Life Applications of Machine Learning

Chapter Five: Machine Learning Algorithms

Chapter Six: Machine learning Projects

Chapter Seven: Artificial Intelligence

Chapter Eight: Glossary

Conclusion

Resources:

Introduction

I want to thank you for choosing this book ‘Machine learning - A Comprehensive, Step-by-Step Guide to Learning and Understanding Machine Learning Concepts, Technology and Principles for Beginners.’

Machines are used in most households and their capabilities have evolved beyond performing manual tasks. There are some countries that use machines in their armies and some companies are using machines to perform some menial tasks. Now, machines can also work on tasks that require some cognition. Human beings were the only ones who had the ability to perform these tasks in the past. Predicting the outcome of tournaments, playing chess, driving cars, diagnosing diseases are some examples of the complex tasks that machines can perform.

However, the remarkable capabilities of machines have instilled fear in some people. They are wary of how powerful machines are and how they can change the world. For example, if you have watched Doctor Who, there are some robots, called Daleks, who wanted to take over the Earth because they were smarter than human beings. Skeptics fear that they may lose their jobs and some fear that the world may be taken over by robots and machines because they are smarter than human beings. The former is a valid fear since there is a possibility that machines can perform your job better than you. The BBC conducted the Will robots take over my job? survey and concluded that jobs like taxi drivers, actuaries, accountants, bar workers and receptionists will be automated soon.

The latter fear is not valid since it is difficult to teach a machine. Learning is a process that includes many smaller processes. In this book, we will look at the different ways a machine can learn. You will notice that the processes used to teach machines are similar to how human beings learn.

Research on automation must be read with a slight level of skepticism since the future of machines and artificial intelligence is unknown. Technology is moving fast, but its adoption is an unchartered path with unforeseen challenges. Machine learning is not simple since it does not only involve turning switches on and off. Machine learning is also not an out–of–the–box solution. Machines operate in parallel to the statistical algorithms, which machine learning engineers and data scientists often oversee. Industry experts believe that there could