Leveraging AI for Signals and Time-Series Applications

Overview

This event has been postponed from 28 September or 6 October.

Deep Learning is a key technology driving the current Artificial Intelligence (AI) megatrend. You may have heard of some mainstream applications of deep learning, but how many of them would you consider applying to your engineering and science applications?

MathWorks developers have purpose-built MATLAB's deep learning functionality for engineering and science workflows. We understand that success goes beyond just developing a deep learning model. Ultimately, models need to be incorporated into an entire system design workflow to deliver a product or a service to the market.

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Highlights

The aim of the session is to provide an overview of how MATLAB enables you to take advantage of disruptive technologies like deep learning for signals and time-series data. We will:

Show where deep learning is being applied in engineering and science, and how its driving MATLAB's development.
Demonstrate a workflow for how you can research, develop and deploy your own deep learning application.
Outline what MathWorks engineers can do to help support you achieve success with deep learning.

About the Presenter

Elvira Osuna-Highley, Ph.D. is a principal customer success engineer with MathWorks, where she supports faculty and researchers with integrating computational tools into their work. Before joining MathWorks, she was on the faculty of the Computational Biology Department at Carnegie Mellon University. She holds a doctorate in biomedical engineering from Carnegie Mellon University, where her research involved applying machine learning techniques to fluorescence microscope images.

Product Focus

Leveraging AI for Signals and Time-Series Applications

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