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

Visualizing data


There are a number of reasons for why we visually represent the data. At the data exploration stage, we can gain an immediate understanding of data properties. Visual representation serves to highlight patterns in data and suggest modeling strategies. Exploratory graphs are usually made quickly and in large numbers. We are not so much concerned with aesthetic or stylistic issues, but we simply want to see what the data looks like.

Beyond using graphs to explore data, they are a primary means of communicating information about our data. Visual representation helps clarify data properties and stimulate viewer engagement. The human visual system is the highest bandwidth channel to the brain, and visualization is the most efficient way to present a large amount of information. By creating a visualization, we can immediately get a sense of important parameters, such as the maximum, minimum, and trends that may be present in the data. Of course, this information can be extracted...