Fashion-MNIST Classification Model (Collaborative Notebook)

This repository contains a collaborative Jupyter notebook showcasing a classification model for the Fashion-MNIST dataset.

About the Fashion-MNIST dataset

Fashion-MNIST is a dataset of 70,000 grayscale images of 10 fashion categories, commonly used as a benchmark for machine learning algorithms. Each image has a size of 28x28 pixels.

The 10 categories in the Fashion-MNIST dataset are:

T-shirt/top
Trouser
Pullover
Dress
Coat
Sandal
Shirt
Sneaker
Bag
Ankle boot

About the notebook

The Jupyter notebook in this repository includes code snippets and visualizations demonstrating data preparation, model creation, and evaluation for the Fashion-MNIST dataset.

The notebook is a collaborative effort between contributors, and can be used as a starting point for building and testing your own classification model for the Fashion-MNIST dataset.

How to use the notebook

To use the notebook, follow these steps:

Clone the repository to your local machine.
Open the Jupyter notebook in a Jupyter environment.
Run the code cells in order to load the Fashion-MNIST dataset, preprocess the data, create the model, and evaluate the performance.
Modify the code cells as needed to experiment with different models, preprocessing techniques, and evaluation metrics.
Share your modifications and improvements with the community by submitting a pull request.

Contributing

Contributions to this repository are welcome and encouraged. To contribute, please follow these steps:

Fork the repository to your own GitHub account.
Clone the forked repository to your local machine.
Create a new branch for your changes.
Make changes to the Jupyter notebook as desired.
Commit your changes and push them to your forked repository.
Submit a pull request to the original repository.

License