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Machine Learning with MATLAB

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Date:  Fri, September 22, 2023
Time:  10:00am - 11:30am
Location:  Holmes Hall 389
Speaker:  Timothy Kyung, MathWorks


Engineers and data scientists work with large amounts of data in a variety of formats such as sensor, image, video, telemetry, databases, and more. They use machine learning to find patterns in data and to build models that predict future outcomes based on historical data. 

In this session, we explore the fundamentals of machine learning using MATLAB. We introduce machine learning techniques available in MATLAB to quickly explore your data, evaluate machine learning algorithms, compare the results and apply the best technique to your problem. 

Highlights include: 

✨ Training, evaluating, and comparing a range of machine learning models 
✨ Using refinement and reduction techniques to create models that best capture the predictive power of your data 
✨ Running predictive models in parallel using multiple processors to expedite your results 
✨ Deploying your models to production in a variety of formats 


Timothy Kyung is an Application Engineer supporting the Government and Department of Defense industry with technical focuses in deployment/interfacing with 3rd party software and parallelization. He holds a B.S. and M.S. in Mechanical Engineering with a focus in robotics from Carnegie Mellon University.

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