- Introduction: Familiarize yourself with Deep Learning concepts and the course.
- Using Pretrained Networks: Perform classifications using a network already created and trained.
- Managing Collections of Image Data: Organize and process images to make them usable with a given network.
- Performing Transfer Learning: Modify a pretrained network to classify images into specified classes.
- Conclusion: Learn next steps and give feedback on the course.
Overview
Syllabus
- Deep Learning for Image Recognition
- Course Example - Identify Objects in Some Images
- Making Predictions
- CNN Architecture
- Investigating Predictions
- Image Datastores
- Preparing Images to Use as Input
- Processing Images in a Datastore
- Create a Datastore Using Subfolders
- What is Transfer Learning
- Components Needed for Transfer Learning
- Preparing Training Data
- Modifying Network Layers
- Setting Training Options
- Training the Network
- Evaluating Performance
- Transfer Learning Summary
- Project - Roundworm Vitality
- Additional Resources
- Survey
Taught by
Renee Bach
