ANN with Pytorch On Pima Diabetes Dataset

This project implements an Artificial Neural Network (ANN) using PyTorch to classify patients as diabetic or non-diabetic based on the Pima Indians Diabetes Dataset, which includes health features like glucose level, BMI, and blood pressure.
The project involves preprocessing the dataset, building a feedforward ANN, training the model on patient data, and evaluating its performance on classifying diabetes cases.
The model’s training progress is tracked through the loss function, and the loss curve is visualized to demonstrate the network’s learning over multiple epochs.

The model’s training progress is tracked through the loss function, and the loss curve is visualized to demonstrate the network’s learning over multiple epochs.