atienosonia/CEMA-Africa

This project uses the malaria dataset from Tensorflow to predict whether a blood cell has the malaria parasite # Malaria Parasite Detection ## :derelict_house: Structure This repository is organised by folders: - Figures: Contains a collection of visualizations presented in PNG format.. - Notebooks: Houses the jupyter notebook file where most of the development took place. ## Model Abstract The model predicts whether a cell image is parasitized or not.The model architecture consists of convolutional layers for feature extraction, batch normalization for stabilization, max-pooling layers for down-sampling, fully connected layers for classification, and a final sigmoid output layer for binary classification (malaria detection). ## Data - The Dataset used was Malaria Dataset obtained from Tensorflow Datasets. - The Dataset contains 27,558 cell images ## References - Publication ## License All the code in this repository is licensed under a GPLv3 License.