Hands-on AI workshop: Introduction to deep learning

Artificial Intelligence techniques like deep learning are introducing automation to the products we build and the way we do business. These techniques can be used to solve complex problems related to images, signals, text and controls. Deep learning can achieve state-of-the-art accuracy in many human-like tasks, such as naming objects in a scene or recognizing optimal paths in an environment. The main tasks involved in deep learning are to assemble large data sets, create a neural network, to train, visualize, and evaluate different models, using specialized hardware - often requiring unique programming knowledge. These tasks are frequently even more challenging because of the complex theory behind them.

In this hands-on lab, you will write code and use MATLAB® Online™ to:

• Train deep neural networks on GPUs in the cloud.
• Create deep learning models from scratch for image and signal data.
• Explore pretrained models and use transfer learning.
• Perform classification tasks on images and signals
• Explore deep learning applications such as ECG classification and pixel-level semantic segmentation on images

Who Should Attend

This workshop is for researchers in all stages of their careers, from student to experienced professors.

About the Presenter

Dr. Kathi Kugler is part of the Academia team at MathWorks. Prior to joining MathWorks, Kathi was working as researcher in the Neuroscience department of LMU Munich, exploring the mammalian auditory system.