Deep Learning with Images in MATLAB

Content

Flipped Classroom: Online Training & Live Session

Online Training: Self-paced, approximately 2 hours

Live Session: Tuesday June 6^th, 2 PM – 3:30 PM (90 minutes)

Instructor: Dr. Franziska Albers, The MathWorks Academia Team

 

In this training you will learn how to apply deep learning in MATLAB using image classification as an example.

We will use a flipped classroom style: you will work through the online course “Deep Learning Onramp” on your own and afterwards we will meet for a live session.

The online course covers:

• Basic idea of deep learning

• Basics of convolutional neural networks

• How to make predictions with pretrained networks

• How to manage collections of image data

• How to perform transfer learning to fine-tune a pretrained network with your own data

In our live session we will:

• Discuss your questions

• Discuss how to build a convolutional neural network from scratch

• Use a convolutional neural network for regression

• Discuss how you can learn more – so you can tackle your own deep learning projects in MATLAB

Prerequisites

You will need a MathWorks account and some basic MATLAB skills to join this training. You are expected to complete the Deep Learning Onramp before joining the live session. The onramp takes approximately two hours to complete.

Who is this for?

The training is for students and researchers who want to get started with deep learning in MATLAB. This training will enable you to solve simple classification and regression problems in MATLAB.