Machine Learning with MATLAB
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
Date and Time
Location
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Registration
- Date: 09 Nov 2023
- Time: 06:30 PM UTC to 07:30 PM UTC
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Speakers
Dr. Neha Sardesai
Biography:
Dr. Neha Sardesai is a Senior Education Application Engineer. She partners with university customers to understand their technical and business challenges and identifies how MathWorks products can help address these challenges in education and research. She demonstrates the value of MATLAB and Simulink to grow their adoption in curriculum, research, and commercial projects. She received her Ph.D. in Electrical Engineering with a focus on Biomedical Instrumentation from the University of Maryland, Baltimore County in 2016. She has been working at MathWorks for 6 years.