This project uses a TinyVGG16-based CNN to classify MRI scans for Alzheimer's Disease stages: Mild Impairment, Moderate Impairment, No Impairment, and Very Mild Impairment. It includes Jupyter notebooks for training and prediction, and a Streamlit app for easy inference. The model achieves high metrics in predicting Alzheimer's stages.

Deep learning project for ocular eye disease classification

TinyVGG model with PyTorch

Food image classification using PyTorch with TinyVGG and EfficientNetB0 on a subset of the Food101 dataset.

This notebook demonstrates the process of building and training a convolutional neural network (CNN) to classify images from the Fashion MNIST dataset. The Fashion MNIST dataset consists of 60,000 training images and 10,000 testing images of clothing items, each labeled with one of 10 categories.

This is the repository for kaggle competition conducted by Annam AI. Contains solutions for 2 challenges

Hi, this a little notebook of a Computer Vision Neural Network to make predictions on three classes (kind of rubbish) using a model based on the TinyVGG.