/--Deep-Learning-for-Fashion-MNIST--Accessory-Classification-Project

This repository contains Python code to classify fashion items using a Convolutional Neural Network (CNN) implemented with TensorFlow and Keras. It includes data preprocessing, model building, training, evaluation, and visualization of results.

Primary LanguageJupyter Notebook

Deep Learning for Fashion-MNIST: Accessory Classification Project

This repository contains Python code to classify fashion items using a Convolutional Neural Network (CNN) implemented with TensorFlow and Keras. It includes data preprocessing, model building, training, evaluation, and visualization of results.

Prerequisites

Before running the code, make sure you have the following libraries installed:

  • numpy
  • matplotlib
  • TensorFlow
  • scikit-learn

You can install them via pip:

pip install numpy matplotlib tensorflow scikit-learn

Usage Clone this repository:

git clone https://github.com/your-username/fashion-mnist-cnn.git

Navigate to the project directory:

cd fashion-mnist-cnn

Run the Python script:

python fashion_mnist_cnn.py

Results

Upon running the script, you'll see the following results:

  • Training and testing data shapes.
  • Model summary.
  • Training with data augmentation.
  • Training and validation loss plots.
  • Training and validation accuracy plots.
  • Confusion matrix.
  • Classification report.
  • Final training and validation accuracies.