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What is Ads Exp5 about?

The project focuses on HR Analytics, specifically predicting employee churn and promotion readiness using machine learning techniques. A dataset of 15,000 employee records is utilized to develop a predictive model, with significant emphasis on data-driven strategies for employee retention. Various models, including Logistic Regression, Decision Tree, and KNN, are evaluated for their performance, with Decision Tree yielding the highest accuracy and F1-score.

Author

Hansal Bhangale

Language

EN