Deep Learning is a key technology driving the current Artificial Intelligence (AI) megatrend. These techniques can be used to solve complex problems related to images, signals, text and controls.

The aim of the session is to provide an overview of how MATLAB enables you to take advantage of technologies like deep learning. In this session, you will learn how to:

• Prepare and preprocess training, validation, and test data for deep neural networks
• Create deep learning networks from scratch for image and signal data
• Explore pretrained models and perform transfer learning
• Import and export models from Python frameworks such as Keras and PyTorch
• Improve training accuracy and avoid overfitting

About the Speaker:

Pitambar Dayal is an Application Engineer who focuses on AI, image processing, and signal processing workflows. Prior to his current role, he worked as product a product manager for autonomous systems and a researcher in a neural imaging lab. Pitambar graduated with a B.S. in Biomedical Engineering from New Jersey Institute of Technology.