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R Data Analysis Projects

You're reading from   R Data Analysis Projects Build end to end analytics systems to get deeper insights from your data

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781788621878
Length 366 pages
Edition 1st Edition
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Author (1):
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Gopi Subramanian Gopi Subramanian
Author Profile Icon Gopi Subramanian
Gopi Subramanian
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Table of Contents (9) Chapters Close

Preface 1. Association Rule Mining 2. Fuzzy Logic Induced Content-Based Recommendation FREE CHAPTER 3. Collaborative Filtering 4. Taming Time Series Data Using Deep Neural Networks 5. Twitter Text Sentiment Classification Using Kernel Density Estimates 6. Record Linkage - Stochastic and Machine Learning Approaches 7. Streaming Data Clustering Analysis in R 8. Analyze and Understand Networks Using R

Taming Time Series Data Using Deep Neural Networks

With the advent of the Internet of Things, more and more devices are being added to the World Wide Web every day. Today's world is rapidly becoming inundated with intelligence devices. These devices are producing data at a rapid pace which we have never seen before. The storage cost has significantly come down, allowing companies to store this massive data in a cheap manner. Smart City projects have been kick-started by various governments. These Smart City projects rely heavily on this instrumentation. Technology companies and governments now want to leverage this massive data, generated from these smart devices, to perform analytics and produce data-enabled applications. The end use cases of these analytics are limitless. The data is characterized by three factors: 

  • Volume: The amount of data generated
  • Variety: The...
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