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R Data Analysis Cookbook, Second Edition

You're reading from   R Data Analysis Cookbook, Second Edition Customizable R Recipes for data mining, data visualization and time series analysis

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787124479
Length 560 pages
Edition 2nd Edition
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Authors (3):
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Kuntal Ganguly Kuntal Ganguly
Author Profile Icon Kuntal Ganguly
Kuntal Ganguly
Shanthi Viswanathan Shanthi Viswanathan
Author Profile Icon Shanthi Viswanathan
Shanthi Viswanathan
Viswa Viswanathan Viswa Viswanathan
Author Profile Icon Viswa Viswanathan
Viswa Viswanathan
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Toc

Table of Contents (14) Chapters Close

Preface 1. Acquire and Prepare the Ingredients - Your Data FREE CHAPTER 2. What's in There - Exploratory Data Analysis 3. Where Does It Belong? Classification 4. Give Me a Number - Regression 5. Can you Simplify That? Data Reduction Techniques 6. Lessons from History - Time Series Analysis 7. How does it look? - Advanced data visualization 8. This may also interest you - Building Recommendations 9. It's All About Your Connections - Social Network Analysis 10. Put Your Best Foot Forward - Document and Present Your Analysis 11. Work Smarter, Not Harder - Efficient and Elegant R Code 12. Where in the World? Geospatial Analysis 13. Playing Nice - Connecting to Other Systems

Who this book is for

This book is for data science professionals or analysts who have performed machine learning tasks and now want to explore deep learning and want a quick reference that address the pain points that crop up while implementing deep learning. Those who wish to have an edge over other deep learning professionals will find this book quite useful.

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