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Smarter Decisions - The Intersection of Internet of Things and Decision Science

You're reading from   Smarter Decisions - The Intersection of Internet of Things and Decision Science A comprehensive guide for solving IoT business problems using decision science

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Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781785884191
Length 392 pages
Edition 1st Edition
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Author (1):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
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Table of Contents (10) Chapters Close

Preface 1. IoT and Decision Science FREE CHAPTER 2. Studying the IoT Problem Universe and Designing a Use Case 3. The What and Why - Using Exploratory Decision Science for IoT 4. Experimenting Predictive Analytics for IoT 5. Enhancing Predictive Analytics with Machine Learning for IoT 6. Fast track Decision Science with IoT 7. Prescriptive Science and Decision Making 8. Disruptions in IoT 9. A Promising Future with IoT

Chapter 5. Enhancing Predictive Analytics with Machine Learning for IoT

The predictive stack for analytics is an extremely wide and varied domain. Many ambiguous buzz words and disciplines can be associated with this field. Statistical modeling, machine learning, artificial intelligence, neural networks, deep learning, cognitive computing, and the list goes on. The variety of definitions available for each of these disciplines makes it difficult to articulate the similarities and differences between them. Our initial exercises were aligned towards statistical modeling; we will now focus more on machine learning. The difference between the two is mainly the school that they originate from. Statistical modeling comes from the mathematical school whereas machine learning evolved from computer science.

In this chapter, we'll enhance our predictive analytics skills using cutting-edge machine learning algorithms that will help us predict with better accuracy. From the time we started...

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