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Analytics for the Internet of Things (IoT)

You're reading from  Analytics for the Internet of Things (IoT)

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781787120730
Pages 378 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Andrew Minteer Andrew Minteer
Profile icon Andrew Minteer
LinkedIn
Andrew Minteer is currently the senior director, data science and research at a leading global retail company. Prior to that, he served as the director, IoT Analytics and Machine Learning at a Fortune 500 manufacturing company. He has an MBA from Indiana University with a background in statistics, software development, database design, cloud architecture, and has led analytics teams for over 10 years. He first taught himself to program on an Atari 800 computer at the age of 11 and fondly remembers the frustration of waiting through 20 minutes of beeps and static to load a 100-line program. He now thoroughly enjoys launching a 1 TB GPU-backed cloud instance in a few minutes and getting right to work. Andrew is a private pilot who looks forward to spending some time in the air sometime soon. He enjoys kayaking, camping, traveling the world, and playing around with his six-year-old son and three-year-old daughter.
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Table of Contents (20) Chapters

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Defining IoT Analytics and Challenges IoT Devices and Networking Protocols IoT Analytics for the Cloud Creating an AWS Cloud Analytics Environment Collecting All That Data - Strategies and Techniques Getting to Know Your Data - Exploring IoT Data Decorating Your Data - Adding External Datasets to Innovate Communicating with Others - Visualization and Dashboarding Applying Geospatial Analytics to IoT Data Data Science for IoT Analytics Strategies to Organize Data for Analytics The Economics of IoT Analytics Bringing It All Together

R (the pirate's language...if he was a statistician)

R is an open source statistical programming language. It has a wide variety of powerful libraries that are simple to download and plug into your analytics code. The packages are developed and maintained by a large community of statisticians and data scientists. It is very powerful and is continuously enhanced with new packages, which are released frequently.

Installing R and RStudio

If you do not have R, install the latest version from https://cran.rstudio.com/. Then, install RStudio, an Integrated Development Environment (IDE) for R, from https://www.rstudio.com/products/rstudio/download/. Both are open source and free to download and use. RStudio is managed by the RStudio company, based in Boston, which also offers paid support and an enterprise version of the software.

Using R for statistical analysis

For this example, we will use the datasets package, which has a wide variety of sample datasets. In RStudio, use the Packages tab to verify...

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Authors (1)

Profile icon Andrew Minteer
LinkedIn
Andrew Minteer is currently the senior director, data science and research at a leading global retail company. Prior to that, he served as the director, IoT Analytics and Machine Learning at a Fortune 500 manufacturing company. He has an MBA from Indiana University with a background in statistics, software development, database design, cloud architecture, and has led analytics teams for over 10 years. He first taught himself to program on an Atari 800 computer at the age of 11 and fondly remembers the frustration of waiting through 20 minutes of beeps and static to load a 100-line program. He now thoroughly enjoys launching a 1 TB GPU-backed cloud instance in a few minutes and getting right to work. Andrew is a private pilot who looks forward to spending some time in the air sometime soon. He enjoys kayaking, camping, traveling the world, and playing around with his six-year-old son and three-year-old daughter.
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See other products by Andrew Minteer

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