Demo: Retail Use Case - FashionMNIST dataset, two CNNs in AI Studio

This project compares two convolutional neural network architectures on the Fashion MNIST dataset:

• SimpleCNN: A basic CNN with 2 convolutional layers.
• DeeperCNN: A deeper CNN with 4 convolutional layers.

The goal is to evaluate and visualize the marginal performance differences between these models using accuracy, loss, ROC curves, and probability-based visualizations.
 

How to Run

1. Create New AIS Project
    
2.  Install dependencies:

   pip install -r requirements.txt3. Run the notebook: Open fashion_mnist_comparison.ipynb in Jupyter Lab and execute all cells sequentially.

Resources:

https://github.com/HPInc/aistudio-samples/tree/main/hackathon-sample-projects/hackathon-retail-MNIST