👋 Mohammed here, friends call me Mo. I am a CS 💻 freshman at Grambling State University. I’m on a journey to build the world’s 🌐 largest reservoir of clean medical 🩺 data and light-weight tools for disease diagnosis. Currently leading a team to create a marketplace (gsuhub) 🛒 for fellow students on my campus. When I am not playing with databases 📇 using SQL, you’ll find me playing Fortnite 🎮 or pondering on "how much is too much" 🤓
My favorite languages for systems programming, software engineering, and data analysis.
My preferred frameworks and technologies for front-end web development and component design.
Stacks I use for back-end web programming and database architecture.
Communitites and tools for version control, code editing, and container orchestration.
I am developing a machine learning model to assist medical professionals in detecting brain tumors, using YOLOv8 as the base object detection model. This project allows me to refine my skills in data annotation, model training, and evaluation, aiming to enhance diagnostic accuracy and support healthcare professionals in early tumor detection.
Check it out!I built a TensorFlow Keras model to classify diseases in maize plants from images, trained on a dataset of 2,500 images. The model is capable of detecting diseases such as Blight and Common Rust. This project has the potential to assist farmers in identifying and diagnosing plant diseases, ultimately helping them manage and mitigate crop issues more effectively.
Try DemoI developed the Nasari website, a platform designed to facilitate seamless transactions and interactions for local farmers. The website features a user-friendly interface built with React and Tailwind CSS, including functionalities for secure user authentication, payment processing with Stripe, and an admin panel for managing market products and vendor listings. This project aims to improve market accessibility and streamline operations for local farmers.
Github Code- I am building tools to detect malaria and other diseases, and also hold the world's largest medical data.