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R Data Science Essentials

You're reading from  R Data Science Essentials

Product type Book
Published in Jan 2016
Publisher
ISBN-13 9781785286544
Pages 154 pages
Edition 1st Edition
Languages

Table of Contents (15) Chapters

R Data Science Essentials
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started with R 2. Exploratory Data Analysis 3. Pattern Discovery 4. Segmentation Using Clustering 5. Developing Regression Models 6. Time Series Forecasting 7. Recommendation Engine 8. Communicating Data Analysis Index

About the Reviewers

Jeremy Gray is a data scientist with over 8 years of experience and is based in Toronto.

He completed his PhD in biology at the University of Auckland (the birthplace of R) and worked as a post-doctoral fellow and course instructor at the University of Toronto. His research interests are primarily in using R as an integrated machine learning environment, financial modeling, and consumer analytics, as well as pedagogical methods in scientific computing.

Navin K Manaswi is a data science professional who loves to delve into messy complex data to bring meaningful insights out of it. Although he has been recognized as one of the top 10 data scientists in India, he still loves to learn everyday as a curious child does. Having done both his bachelor's and master's from IIT Kanpur, he has been contributing to the world of data analytics, machine learning, big data technologies, and business intelligence. So far, he has worked at the intersection of technologies and business domains of supply chain management, sales and marketing, finance, and healthcare.

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