Learn how to train image classification models using PyTorch on Jetson Nano, including transfer learning, re-training models on custom datasets, and testing models on live data streams and camera feeds. The course covers steps such as downloading data, exporting models to Onyx, and practical applications of image classification. Intended for individuals interested in AI, machine learning, and computer vision, with a focus on deploying models on edge devices like Jetson Nano.
Jetson AI Fundamentals - Training Image Classification Models
Overview
Syllabus
- Introduction - Training Image Classification Models
- Getting Started - Transfer Learning with PyTorch
- Example 1 - Re-training on Cat/Dog Dataset
- Example 1 - Step 1: Downloading the data
- Re-training ResNet-18 Model
- Exporting Pytorch model to Onyx and testing the model
- Testing on a live data stream
- Training on a custom dataset
- Testing the trained model on a live camera feed
- Conclusion
Taught by
NVIDIA Developer
