This project implements a Convolutional Neural Network (CNN) Classifier designed to predict whether a given patient has diabetes based on input medical data.
The model is constructed using the Keras deep learning framework, utilizing Convolutional Neural Network architecture to process and analyze medical data for diabetes prediction.
- Keras Framework: The CNN model is implemented using Keras, a high-level neural networks API.
- Pandas for Data Processing and Cleaning: Pandas is used extensively for data manipulation, cleaning, and preprocessing.
- Feature Scaling with Standard Scaler: Sklearn's Standard Scaler is utilized for feature scaling to normalize the data.
- Previously Trained Models and Training Data: The repository includes pre-trained models and the training dataset for reference and reproduction of results.
The repository contains the following structure:
models/
: Includes saved trained models in H5 format.data/
: Contains the training dataset.