Neural Network Testing App

A neural network for the MNIST dataset, built and deployed using Streamlit. This app allows users to experiment with different network architectures, train models, and visualize the results.

Key Features:

Customizable Architecture: Adjust the number of hidden layers and units per layer.

Training & Evaluation: Train the model on the fly and evaluate its performance on training and validation sets.

Insights: Get feedback on whether the model is overfitting, underfitting, or well-balanced.

This project was a great opportunity to deepen my understanding of neural networks and deployment using Streamlit. It also provided hands-on experience in visualizing model performance and making data-driven decisions.

Check out my code here: https://lnkd.in/dGBG5C7B