Deep Learning Onramp
Access to MATLAB through your web browser
Engaging video tutorials
Hands-on exercises with automated assessments and feedback
Lessons available in English and Japanese
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1.
Introduction
Familiarize yourself with Deep Learning concepts and the course.
- Deep Learning for Image Recognition
- Course Overview
2.
Using Pretrained Networks
Perform classifications using a network already created and trained.
- Course Example - Identify Objects in Some Images
- Making Predictions
- CNN Architecture
- Investigating Predictions
- Image Datastores
3.
Managing Collections of Data
Import folders of images and make them usable with a given network.
- Image Datastores
- Preparing Images to Use as Input
- Processing Images in a Datastore
- Modifying Network Layers
- Create a Datastore Using Subfolders
4.
Performing Transfer Learning
Modify a pretrained network to classify images into specified classes.
- 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
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