Project-Compozent

An interactive Machine Learning-powered web application that predicts whether a person is diabetic based on key health parameters. Built with Python, Scikit-learn, and Streamlit, this app aims to make early diabetes risk detection simple and accessible.

An interactive Machine Learning-powered web application that predicts whether a person is diabetic based on key health parameters. Built with Python, Scikit-learn, and Streamlit, this app aims to make early diabetes risk detection simple and accessible.

An algorithmic trading strategy incursion using Adaboost machine learning classifier, to create the first volatility security suitable for long term investors.

Classification Project for SDAIA T5 Data Science Bootcamp. This project will choose the best classification model to predict whether a loan is a short-term loan or a long-term loan, based on some features.

learning python day 15

Practicum by Yandex Project 7: In this supervised learning project, we are to use customer data and develop a model that would predict whether a customer will leave a bank soon. One of the objective is to build a machine learning model with the maximum possible F1 score of atleast 0.59 or higher.

A machine learning–based application for early detection of liver disease using patient health parameters. The system preprocesses clinical data, trains a predictive model with scikit-learn, and integrates LIME for model explainability. A FastAPI backend exposes RESTful endpoints for predictions and interpretability reports.

NeuroDetect AI is a deep-learning based system that detects brain tumors and Alzheimer’s disease from MRI scans using optimized CNN and transfer-learning models. It provides fast and reliable predictions through a simple web interface with a Flask backend, offering an effective AI solution for early neurological diagnosis.

Telecome-Churn-PCA-And-Multiple-Models