Ben MacKenzieBilal Paracha

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Improving industrial monitoring with deep learning

Analyzing real-time sensor data from your facility

Wednesday, June 20, 2018
10:00am PT | Show Timezones...

Add to Calendar 06/20/2018 10:00 06/20/2018 11:00 America/Los_Angeles Webcast: Improving industrial monitoring with deep learning Online Go to the webcast O'Reilly Media MM/DD/YYYY

Presented by: Ben MacKenzie, Bilal Paracha

Duration: Approximately 60 minutes.

Cost: Free

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As the cost of sensors and data storage plummets, manufacturers are mounting video and still image cameras throughout their facilities, harvesting massive amounts of rich-media time series data.

We describe a new data and analytics architecture that enables significant improvements in ongoing operational “Industrial Inspection.” Critical to the success of our efforts is a hybrid, extensible analytic architecture integrating diverse big data, and diverse analytics including deep learning. Based on our experiences with large customers, we identify core challenges to the effective use of new data and analytics, and detail how time-series image data can be used to engineer vastly improved predictions of production flaws and poor quality, thus improving yield and competitive advantage.

In this webcast, you’ll learn:

  • The critical issues in managing and integrating time-series image data flows.
  • Approaches to applying deep learning to industrial process monitoring challenges.
  • Priorities to keep in mind when pursuing large-scale projects involving sensor data and deep learning.


Ben MacKenzie, Director AI Engineering at Think Big Analytics

Bilal Paracha, Teradata Industrial Intelligence at Think Big Analytics