Key Features Explore real-world use cases from the Internet of Things (IoT) domain using decision science with this easy-to-follow, practical bookLearn to make smarter decisions on top of your IoT solutions so that your IoT is smart in a real senseThis highly practical, example-rich guide fills the gap between your knowledge of data science and
Explore real-world use cases from the Internet of Things (IoT) domain using decision science with this easy-to-follow, practical bookLearn to make smarter decisions on top of your IoT solutions so that your IoT is smart in a real senseThis highly practical, example-rich guide fills the gap between your knowledge of data science and IoT
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 of a problem and the 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
Explore decision science with respect to IoTGet to know the end to end analytics stack – Descriptive + Inquisitive + Predictive + PrescriptiveSolve problems in IoT connected assets and connected operationsDesign and solve real-life IoT business use cases using cutting edge machine learning techniquesSynthesize and assimilate results to form the perfect story for a businessMaster 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
Jojo Moolayil is a Data Scientist with over 3 years of extensive and varied experience in the field of Internet of Things, decision science, machine Learning, and big data analytics. He has worked with industry leaders to provide analytical solutions for business problems. His experience in the analytics industry is mainly with Mu Sigma Inc. and Flutura Decision Sciences and Analytics.
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