SLIDES: Deep Learning with TensorFlow in IoT World for Predictive Maintenance by Justin Brandenburg

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Slides of the talk by Justin Brandenburg on deep learning with tensorflow at the Chicago Advanced Analytics Meetup on October 12th 2017. 

"As MapR continues to innovate its Converged Data Platform and how it integrates a globally distributed elastic data plane that not only supports distributed file processing but also strongly consistent geo-distributed database applications with high performance NoSQL document DB, and real-time event streaming capabilities in a single cluster, MapR will provide a technical deep dive into these innovations.

In this talk, we'll look at how organizations can leverage IoT and bring compelling insight into their operations to optimize efficiencies or predict behavior with actionable results with MapR Converged Platform and Deep Learning Models.

We will evaluate and demonstrate a workflow for an IoT predictive maintenance scenario that leverages real-time streaming events and predict behavior using TensorFlow, Spark and Python. We will showcase an entire data pipeline build for data transformation, model training/testing, and data visualization of results."