How to optimize Physical Assets with Machine Learning

Date: Thursday, June 27, 2019
Time: 1:30–2:20PM 
Location: TBD

 

Using a real-world case study from the oil & gas industry, this session dives deep into applying Machine Learning to sensor time series data to demonstrate how to sample a time series dataset to generate training and validation datasets, parallelize compute intensive feature creation to handle the volume and velocity of sensor data, apply classic ML techniques, and the results of the case study.

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Speaker:
Rajendra Koppula, Director of Machine Learning