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Thursday, February 27 • 2:30pm - 3:20pm
DPP: Data Preprocessing Pipeline Tool For Enhanced IoT Prognostic ML Use Cases

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There are increasing requests from customers for advanced prognostic ML techniques for predictive maintenance use cases for many industrial segments Oracl serves. The greatest challenges for applying any types of Oracle (or 3rd party) ML techniques for time-series prognostics do not have to do with the technique selected (including NNs, SVMs, Kernel Regression, MSET2, etc). Rather, the greatest challenges have to do with sensor and signal issues that occur across all IoT industries... e.g. disparate sampling rates, missing values, quantized signals, decalibration bias in sensors, and many others that will be presented. OracleLabs has developed a suite of Oracle-patented algorithms that detect and autonomously correct these and other common sensor and signal challenges. These Intelligent Data Preprocessing algorithms have been incorporated into a new Data Preprocessing Pipeline (DPP) tool/framework that will be presented with numerous examples from real industrial use cases.

avatar for Kenny  Gross

Kenny Gross

Architect, Oracle
Kenny C Gross, PhD, is an AI Architect in Oracle's Physical Sciences Research Center in San Diego, CA. Kenny specializes in advanced pattern recognition and prognostic anomaly discovery for Big Data applications in IoT industries, life sciences, and business business-critical data... Read More →

Thursday February 27, 2020 2:30pm - 3:20pm PST
Bldg 23- Rm 1730 .