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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.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781783280995
Length 360 pages
Edition 1st Edition
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Author (1):
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Hector Cuesta Hector Cuesta
Author Profile Icon Hector Cuesta
Hector Cuesta
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Toc

Table of Contents (24) Chapters Close

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

Modeling with cellular automata


Cellular automaton are mathematical and computational discrete models created by John von Neumann and Stanislaw Ulam. CA is represented as a grid where in each cell a small computation is performed. In CA we will share the process through all the small cells in the grid. CA shows behavior similar to biological reproduction and evolution. In this case, we can say that each cell is an individual in our population (grid) that will switch between states depending on its social interaction (contact rate). (Refer to SIR and SIRS models).

Seen as discrete simulations of dynamical systems, CA has been used for modeling in different areas such as traffic flow, encryption, growth of crystals, bird migration, and epidemic outbreaks. Stephen Wolfram, one of the most influential researchers in CA describes CA as follows:

"Cellular automata are sufficiently simple to allow detailed mathematical analysis, yet sufficiently complex to exhibit a wide variety of complicated phenomena...

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