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Smarter Decisions – The Intersection of Internet of Things and Decision Science
Author: Jojo Moolayil
Pub Date: 2016
Publisher: Packt Publishing
ISBN: 978-1-78588-419-1
Pages: 392
Language: English
Format: PDF/EPUB
Size: 18 Mb
With an increasing number of devices getting connected to the Internet, massive amounts of data are being generated that can be used for analysis. This book helps you to understand Internet of Things in depth and decision science, and solve business use cases. With IoT, the frequency and impact of the problem is huge. Addressing a problem with such a huge impact requires a very structured approach.The entire journey of addressing the problem by defining it, designing the solution, and executing it using decision science is articulated in this book through engaging and easy-to-understand business use cases. You will get a detailed understanding of IoT, decision science, and the art of solving a business problem in IoT through decision science.By the end of this book, you’ll have an understanding of the complex aspects of decision making in IoT and will be able to take that knowledge with you onto whatever project calls for itWhat You Will Learn
- Explore decision science with respect to IoT
- Get to know the end to end analytics stack – Descriptive + Inquisitive + Predictive + Prescriptive
- Solve problems in IoT connected assets and connected operations
- Design and solve real-life IoT business use cases using cutting edge machine learning techniques
- Synthesize and assimilate results to form the perfect story for a business
- Master the art of problem solving when IoT meets decision science using a variety of statistical and machine learning techniques along with hands on tasks in R
If you have a basic programming experience with R and want to solve business use cases in IoT using decision science then this book is for you. Even if your’re a non-technical manager anchoring IoT projects, you can skip the code and still benefit from the book.
Enter the world of Internet of Things with the power of data science with this highly practical, engaging book
Table of Contents
1: IoT and Decision Science
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
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