Book Image

Designing Machine Learning Systems with Python

By : David Julian
Book Image

Designing Machine Learning Systems with Python

By: David Julian

Overview of this book

Machine learning is one of the fastest growing trends in modern computing. It has applications in a wide range of fields, including economics, the natural sciences, web development, and business modeling. In order to harness the power of these systems, it is essential that the practitioner develops a solid understanding of the underlying design principles. There are many reasons why machine learning models may not give accurate results. By looking at these systems from a design perspective, we gain a deeper understanding of the underlying algorithms and the optimisational methods that are available. This book will give you a solid foundation in the machine learning design process, and enable you to build customised machine learning models to solve unique problems. You may already know about, or have worked with, some of the off-the-shelf machine learning models for solving common problems such as spam detection or movie classification, but to begin solving more complex problems, it is important to adapt these models to your own specific needs. This book will give you this understanding and more.
Table of Contents (16 chapters)
Designing Machine Learning Systems with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Free Chapter
1
Thinking in Machine Learning
Index

Chapter 4. Models – Learning from Information

So far in this book, we have examined a range of tasks and techniques. We introduced the basics of data types, structures, and properties, and we familiarized ourselves with some of the machine learning tools that are available.

In this chapter, we will look at three broad types of model:

  • Logical models

  • Tree models

  • Rule models

The next chapter will be devoted to another important type of model—the linear model. Much of the material in this chapter is theoretical, and its purpose is to introduce some of the mathematical and logical tools needed for machine learning tasks. I encourage you to work through these ideas and formulate them in ways that may help solve problems that we come across.