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Lazy Predict 2.0 to help you benchmark models without much code and understand what works better without any hyyper-parameter tuning.
This repository features a comprehensive ML pipeline for supervised learning tasks, covering data collection, cleaning, EDA, feature engineering, model training, and evaluation.
Efficient employee attrition prediction using LazyPredict to evaluate and compare multiple classification models for HR analytics.
A comprehensive project analyzing heart attack risk factors through exploratory data analysis and machine learning to predict and provide actionable healthcare insights.