modelcomparison

This project implements various machine learning algorithms to classify diseases such as diabetes, brain stroke, and heart disease. It compares the performance of these models, providing insights into their effectiveness, along with an interactive visualization dashboard and a RESTful API for model training and evaluation.

Deep learning pipeline for geospatial land classification from satellite imagery. Benchmarks CNNs, Vision Transformers, and hybrid CNN-ViT architectures across Keras/TensorFlow and PyTorch — with reproducible training, comprehensive evaluation, and framework trade-off analysis.