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[Tutorial] Building Machine Learning Models for Predictive Maintenance Applications

A session at PAPIs '15

  • Yan Zhang

Thursday 6th August, 2015

2:30pm to 3:10pm (EST)

This talk introduces the landscape and challenges of predictive maintenance applications in the industry, illustrates how to formulate (data labeling and feature engineering) the problem with three machine learning models (regression, binary classification, multi-class classification) using a publicly available aircraft engine run-to-failure data set, and showcases how the models can be conveniently trained and compared with different algorithms in Azure ML.

About the speaker

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Yan Zhang

Data Scientist at Microsoft

Dr. Yan Zhang is a data scientist in Microsoft Cloud & Enterprise Azure Machine Learning product team. She builds predictive models and generalize data driven solutions on Cloud machine learning platform. Her recent research include predictive maintenance in IoT applications, customer segmentation, and text mining. Dr. Zhang holds a Ph.D. in computer science majoring in data mining.

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PAPIs '15

Australia Australia, Sydney

6th7th August 2015

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When

Time 2:30pm3:10pm EST

Date Thu 6th August 2015

Short URL

lanyrd.com/sdpkhx

Official event site

www.papis.io/2015

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