Overview

Are you new to machine learning and deep learning? Do you want to apply them in your engineering projects? Machine learning is about letting computers learn from data without being explicitly programmed with a fixed model. Deep learning, on the other hand, is a subset of machine learning that uses neural networks with many hidden layers. These neural networks learn directly from raw data and can sometimes outdo traditional machine learning algorithms in terms of accuracy.

In our hands-on workshop, you'll discover how to harness machine learning and deep learning for images and signals. Dive into MATLAB® where you can deploy advanced machine learning and deep learning techniques effortlessly, even without much coding or prior experience in your engineering applications. Let's get you started on this exciting journey!

Highlights

• Master the basics of machine learning and deep learning and understand keywords like "supervised learning", "feature extraction", "feature selection", “networks”, and “hyperparameter tuning”.
• Create and test your machine learning models and deep neural networks to work with images and signals.
• Integrate AI models from other frameworks into your applications.
• Grasp the key differences between machine learning and deep learning and understand when to use each.
• Deploy your AI model into an engineering system.

Who Should Attend

• UG, PG Students
• PhD Scholars
• Faculty

About the Presenter

Dr. Monalisa Pal, Senior Customer Success Engineer, MathWorks

Ms. Nisha M, Customer Success Specialist, MathWorks