This project uses Logistic Regression on the Wisconsin Breast Cancer Dataset (569 samples, 30 features) to predict tumor malignancy, integrated into a Streamlit app for real-time diagnosis.
This Project is a Streamlit web app that calculates Beta and Returns for selected stocks using the Capital Market Pricing Model (CMPM).
Determining the type of Erythemato-Squamous Disease using Machine Learning Algorithms
The primary goal of this C++ project is to assist a farmer in harvesting cotton without waste while also reducing transportation costs and time.