Book Image

Building Machine Learning Systems with Python - Second Edition

By : Luis Pedro Coelho, Willi Richert
Book Image

Building Machine Learning Systems with Python - Second Edition

By: Luis Pedro Coelho, Willi Richert

Overview of this book

<p>Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python is a wonderful language to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation. With its excellent collection of open source machine learning libraries you can focus on the task at hand while being able to quickly try out many ideas.</p> <p>This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and introducing libraries. You’ll quickly get to grips with serious, real-world projects on datasets, using modeling, creating recommendation systems. Later on, the book covers advanced topics such as topic modeling, basket analysis, and cloud computing. These will extend your abilities and enable you to create large complex systems.</p> <p>With this book, you gain the tools and understanding required to build your own systems, tailored to solve your real-world data analysis problems.</p>
Table of Contents (20 chapters)
Building Machine Learning Systems with Python Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Sketching our roadmap


Sentiment analysis of tweets is particularly hard, because of Twitter's size limitation of 140 characters. This leads to a special syntax, creative abbreviations, and seldom well-formed sentences. The typical approach of analyzing sentences, aggregating their sentiment information per paragraph, and then calculating the overall sentiment of a document does not work here.

Clearly, we will not try to build a state-of-the-art sentiment classifier. Instead, we want to:

  • Use this scenario as a vehicle to introduce yet another classification algorithm, Naïve Bayes

  • Explain how Part Of Speech (POS) tagging works and how it can help us

  • Show some more tricks from the scikit-learn toolbox that come in handy from time to time