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

Summary


In this chapter, we created a basic but useful e-mail subject line tester. This chapter provides a guide on how to code a basic Naïve Bayes classifier from scratch, without any external library, in order to demonstrate how easy it is to program a machine learning algorithm. We also defined a maximum size threshold for the training set and got an accuracy of 92 percent, which for this basic example is quite good.

In the following chapters, we will introduce more complex machine learning algorithms using the mlpy library and we will present how to extract more sophisticated features.