This project demonstrates a machine learning solution for predicting diabetes based on user-provided health data. The application uses Streamlit for an interactive web interface and advanced interpretability tools like SHAP and permutation importance to explain model predictions.
A machine learning service that predicts a user's gender based on transaction data, using behavioral patterns and purchase history to deliver accurate, data-driven insights
The aim of this project is to identify fraudulent credit card transaction using Neural Networks.
Using Random forest to predict employee turnover
our goal for this project is to predict the churn probability of a customer using machine learning classification techniques.
DSA Projects - Artificial Intelligence
Built several predictive machine learning algorithm to predict customer churn.
Logistic regression model predicting 10 year coronary heart disease risk using the Framingham Heart Study dataset. Includes median imputation, feature scaling, and full evaluation with precision, recall, F1, and ROC AUC.
This repository contains the dataset and a python file. The python file contains basic EDA, Label encoding, and Modelling using Logistic Regression. ROC analysis is also included.
Add a description, image, and links to the rocauc topic page so that developers can more easily learn about it.
To associate your repository with the rocauc topic, visit your repo's landing page and select "manage topics."