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Practical Data Analysis

You're reading from Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

Product type Paperback

Published in Oct 2013

Publisher Packt

ISBN-13 9781783280995

Length 360 pages

Edition 1st Edition

Languages

Python

Tools

NLTK

Concepts

Data Analysis

Author (1):

Hector Cuesta

View More author details

Table of Contents (24) Chapters

Practical Data Analysis

Credits

Foreword

About the Author

Acknowledgments

About the Reviewers

www.PacktPub.com

Preface

1. Getting Started FREE CHAPTER

2. Working with Data

3. Data Visualization

4. Text Classification

5. Similarity-based Image Retrieval

6. Simulation of Stock Prices

7. Predicting Gold Prices

8. Working with Support Vector Machines

9. Modeling Infectious Disease with Cellular Automata

10. Working with Social Graphs

11. Sentiment Analysis of Twitter Data

12. Data Processing and Aggregation with MongoDB

13. Working with MapReduce

14. Online Data Analysis with IPython and Wakari

Setting Up the Infrastructure

Index

Appendix A. Setting Up the Infrastructure

This chapter includes instructions for installing and configuring software packages that support all the projects in this book.

In this chapter, we will cover the installations of:

Python 3
IDLE
Numpy
SciPy
mlpy
OpenRefine
MongoDB
UMongo
Gephi

The rest of the chapter is locked

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Authors (1)

Hector Cuesta

Hector Cuesta

Hector Cuesta is founder and Chief Data Scientist at Dataxios, a machine intelligence research company. Holds a BA in Informatics and a M.Sc. in Computer Science. He provides consulting services for data-driven product design with experience in a variety of industries including financial services, retail, fintech, e-learning and Human Resources. He is an enthusiast of Robotics in his spare time. You can follow him on Twitter at https://twitter.com/hmCuesta.

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