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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
 

Walkthrough video: Hackathon-FashionMNIST-retail.mp4
 

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