Book Image

Practical Data Analysis - Second Edition

By : Hector Cuesta, Dr. Sampath Kumar
Book Image

Practical Data Analysis - Second Edition

By: Hector Cuesta, Dr. Sampath Kumar

Overview of this book

Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.
Table of Contents (21 chapters)
Practical Data Analysis - Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface

Chapter 4.  Text Classification

This chapter builds on a brief introduction to text classification and provides you with an example of the Naïve Bayes algorithm, developed from scratch in order to explain how to turn an equation into code.

In this chapter, we will cover:

  • Learning and classification

  • Bayesian classification

  • Naïve Bayes algorithm

  • E-mail subject line tester

  • The data

  • The algorithm

  • Classifier accuracy