Add PyTorch CNN image classification tutorial notebook#70
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- New tutorial notebook aligned with GettingStarted.ipynb structure - CIFAR-10 dataset with subset (10k samples) and 5 epochs for faster training - CNN architecture with conv blocks, batch norm, dropout - Full Patra Model Card workflow: metadata, AIModel, requirements, save/submit - Inference example and optional submission to Patra server
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Summary
Adds a new tutorial notebook for PyTorch CNN image classification, aligned with the structure of
GettingStarted.ipynb.Changes
examples/notebooks/PyTorch_CNN_Image_Classification.ipynbRationale
Provides a parallel tutorial path for PyTorch + image classification (vs. TensorFlow + tabular in GettingStarted), improving discoverability and reproducibility documentation for CNN models.