English | 2016 | ISBN: 1785884191 | 392 Pages | True PDF, EPUB | 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 it
What 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.