October 2016
Intermediate to advanced
87 pages
1h 50m
English
book
The Path to Predictive Analytics and Machine Learning
by Conor Doherty, Steven Camina, Kevin White, Gary Orenstein
Content preview from The Path to Predictive Analytics and Machine Learning
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Chapter 8. Predictive Analytics in Use
There will be numerous applications of predictive analytics and machine learning to real-time challenges with adoption far and wide.
Expanding on the earlier discussion about taking machine learning from batch to real-time machine learning, in this chapter, we explore another use case, this one specific to the Internet of Things (IoT) and renewable energy.
Renewable Energy and Industrial IoT
The market around the Industrial Internet of Things (IIoT) is rapidly expanding, and is set to reach $150 billion in 2020, according to research firm Markets and Markets. According to the firm,
IIoT is the integration of complex physical machinery with industrial networks and data analytics solutions to improve operational efficiency and reduce costs.
Renewable energy is an equally high growth sector. In mid-2016, Germany announced that it had developed almost all of its power from renewable energy (“Germany Just Got Almost All of Its Power From Renewable Energy,” May 15, 2016).
The overall global growth in renewable energy continues at a breakneck pace, with the investment in renewables reaching $286 billion worldwide in 2015 (BBC).
PowerStream: A Showcase Application of Predictive Analytics for Renewable Energy and IIoT
PowerStream is an application that predicts the global health of wind turbines. It tracks the status of nearly 200,000 wind turbines around the world across approximately 20,000 wind farms. With each wind turbine reporting multiple ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.