Model for easy facilitation of visa processing and approvals
An end-to-end data science project in R identifying key drivers of customer churn. Delivers actionable business insights from EDA and predictive models (Logistic Regression, Random Forest) with ~81% accuracy.
IBM HR Analytics Employee Attrition Analysis project exploring key factors behind employee turnover, revealing high-risk roles and demographics, and supporting data-driven retention and workforce planning.
Analyze the used devices dataset, build a model which will help develop a dynamic pricing strategy for used and refurbished devices, and identify factors that significantly influence the price.
Ensemble Techniques: Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.
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