Jeel

Conducted hypothesis testing to reveal a statistically significant difference in average view counts between TikTok videos from verified and unverified accounts, indicating potential behavioral differences.

Designed and implemented a MySQL-based RDBMS for an e-commerce fashion site using Azure Data Studio, reducing query response times by 30% and enhancing performance and user experience.

Conducted a ANOVA hypothesis test to analyze the impact of different TV promotion budget levels on sales using ANOVA, in order to determine whether higher TV promotion budgets lead to significantly higher sales and quantify the estimated differences in sales across different budget levels.

Built a machine learning model to predict whether or not an employee will leave the company.

Performed one way ANOVA and two way ANOVA to test different hypotheisies such as the difference in price of diamonds based on diamond color and cut.

This project focuses on developing and evaluating a churn prediction model to understand and reduce user attrition by leveraging machine learning techniques and feature engineering.