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Designing Machine Learning Systems with Python

Designing Machine Learning Systems with Python

By : David Julian
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Designing Machine Learning Systems with Python

Designing Machine Learning Systems with Python

2 (1)
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 (11 chapters)
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1. Thinking in Machine Learning
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Index

Structured features


We assume that each instance can be represented as a vector of feature values and that all relevant aspects are represented by this vector. This is sometimes called an abstraction because we filter out unnecessary information and represent a real-world phenomena with a vector. For example, representing the entire works of Leo Tolstoy as a vector of word frequencies is an abstraction. We make no pretense that this abstraction will serve any more than a very particular limited application. We may learn something about Tolstoy's use of language and perhaps elicit some information regarding the sentiment and subject of Tolstoy's writing. However, we are unlikely to gain any significant insights into the broad canvas of the 19th century Russia portrayed in these works. A human reader, or a more sophisticated algorithm, will gain these insights not from the counting of each word but by the structure that these words are part of.

We can think of structured features in a similar...

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