The Complete Guide to Understand Python Machine Learning for Beginners and Artificial Intelligence
The first chapter is an introduction to Machine Learning and a history of
where it all began back in the 1940s to where it is at today. The chapter also
covers the terms popular in Machine learning and artificial intelligence
circles and their definitions. This is so that a beginner will understand the
language in the book without much struggle.
The second chapter is about the concept of machine learning. This chapter
offers an in-depth explanation of how machines gain the ability to think for
themselves the same way human beings do and the many ways people
apply machine learning in various fields. It continues to explain the key
elements of machine learning and gives a description of the types of
Artificial Intelligence learning available today.
The third chapter is about the mathematical notation for machine learning,
where the reader will understand the relationship between mathematical
nomenclatures and machine learning. The chapter also explains the
terminologies common in machine learning, and it concludes with a
roadmap for machine learning exploration.
The fourth chapter is an introduction to using Python for machine learning,
and it explains the basics an individual would need to understand about this
excellent coding language. The chapter explains the various stages involved
in machine learning using Python, and it contains real-life explanations of
the integral features and functions making up this language.
The fifth chapter is an explanation of Artificial Neural Networks in machine
learning. This chapter goes into detail to show how the human brain is the
main inspiration for machine learning and how with time machines will
have the ability to reason the same way human beings do. The chapter
explains the meaning of neural networks, the classifiers in Python machine
learning, the machine learning models, and the metrics for evaluating