Lazy Predict Nightly enables rapid benchmarking of machine learning models with just a few lines of code. It helps identify the best-performing algorithms on your dataset without requiring hyperparameter tuning.

This repository showcases an ANN-based project to predict student performance using features like gender, parental education, and test preparation, studied during the Manisa AI and Deep Learning Workshop.

A comprehensive project analyzing heart attack risk factors through exploratory data analysis and machine learning to predict and provide actionable healthcare insights.

Efficient employee attrition prediction using LazyPredict to evaluate and compare multiple classification models for HR analytics.

This repository features a comprehensive ML pipeline for supervised learning tasks, covering data collection, cleaning, EDA, feature engineering, model training, and evaluation.