Educational Course
Hands-On Deep Learning
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Session Topic: Machine Learning for Image Reconstruction
Session Sub-Topic: Hands-On Deep Learning
Weekday Course
ORGANIZERS: Florian Knoll, Michael Lustig, Demian Wassermann
| Wednesday Parallel 5 Live Q&A | Wednesday, 12 August 2020, 15:15 - 16:00 UTC | Moderators: Michael Lustig & Florian Knoll |
Skill Level: Basic
Session Number: M-03
Overview
A hands-on crash course on deep learning that will take you from initial setup to an implementation, experimental design, and reporting of an image classification/image denoising or image synthesis.
Target Audience
Anyone wanting to try deep learning but don't know where to start.
Educational Objectives
As a result of attending this course, participants should be able to:
- Originate an AWS instance installed with Tensor Flow/PyTorch;
- Set up a Jupyter notebook on a browser;
- Demonstrate loading data to be processed;
- Set up a network for classification;
- Explain how to train a network for classification;
- Demonstrate classification and/or image denoising/image synthesis of brain tumors or similar medical image applications;
- Employ cross validation to asses generalization; and
- Use Tensor Flow/PyTorch visualization tools.
| Hands-On Deep Learning (Supporting Presenter)
Hemant Kumar Aggarwal
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| Hands-On Deep Learning
Peter Chang
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| Hands-On Deep Learning (Supporting Presenter)
Chen Qin
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| Hands-On Deep Learning (Supporting Presenter)
Matthew Muckley
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