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

Feature types


There are three distinct types of features: quantitative, ordinal, and categorical. We can also consider a fourth type of feature—the Boolean—as this type does have a few distinct qualities, although it is actually a type of categorical feature. These feature types can be ordered in terms of how much information they convey. Quantitative features have the highest information capacity followed by ordinal, categorical, and Boolean.

Let's take a look at the tabular analysis:

Feature type

Order

Scale

Tendency

Dispersion

Shape

Quantitative

Yes

Yes

Mean

Range, variance, and standard deviation

Skewness, kurtosis

Ordinal

Yes

No

Median

Quantiles

NA

Categorical

No

No

Mode

NA

NA

The preceding table shows the three types of features, their statistics, and properties. Each feature inherits the statistics from the features from the next row it in the table. For example, the measurement of central tendency for quantitative features includes the median and mode...