Book Image

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

By : Jojo Moolayil
Book Image

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

By: Jojo Moolayil

Overview of this book

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 it
Table of Contents (15 chapters)
Smarter Decisions – The Intersection of Internet of Things and Decision Science
Credits
About the Author
About the Reviewer
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Preface

Linear regression - predicting a continuous outcome


There are a variety of statistical techniques available that can be used for prediction. Their usage is defined by the type of the dependent variable (continuous/categorical). A different technique or algorithm is required to solve these two different categories. We can use linear regression to predict a continuous variable and logistic regression for a categorical variable. A plethora of other techniques are available for these cases, but let's start solving the problem of predicting a continuous variable using linear regression.

Prelude

Before we begin understanding what we are going to build, let's take a moment to clearly understand the requirements from John's team and also study about how they plan to use the results. The team needs our help in building a system that can predict the actual quality parameter (Output Quality Parameter 2) before the manufacturing process. The team of technicians and store managers plan the production a...