Image Dimensionality Reduction

This project demonstrates how to perform dimensionality reduction on images using TensorFlow and Keras. The dataset used is the MNIST dataset of handwritten digits.

Requirements

• Python 3.10
• TensorFlow 2.16.1
• NumPy
• Matplotlib

Installation

To install the required packages, run the following command:

pip install tensorflow==2.16.1 numpy matplotlib

Notebook Overview

1. Imports: Import necessary libraries.
2. Load and Preprocess Data: Load the MNIST dataset and preprocess it.
3. Build and Train the Model: Build and train an autoencoder model.
4. Visualize the Results: Visualize the original, encoded, and reconstructed images.

Usage

To run the notebook, execute the cells in the provided order. The notebook will guide you through the process of dimensionality reduction using an autoencoder.

Results

The notebook will display the original, encoded, and reconstructed images to show the effectiveness of the dimensionality reduction process.