Machine Learning Project

This project focuses on two key tasks:

Image Compression: Using machine learning models to reduce the size of image data while retaining essential information.

Anomaly Detection: Identifying unusual patterns in the ECG5000 dataset, a dataset of Electrocardiogram (ECG) readings.

Features

Image Compression: Implementation of deep learning techniques for efficient image representation.

Anomaly Detection: Leveraging machine learning to identify outliers in ECG data.

Data Visualization: Use of plots and visualizations to interpret results effectively.