April 13, 2025
End-to-End ML Project
A complete machine learning case study using real-world customer behavioral data.
Covers ETL, EDA,feature engineering, model training, hyperparameter tuning (GridSearchCV),and performance evaluation...
Developed a machine learning model to predict customer purchase behavior using a Random Forest classifier, achieving a 91% F1 score.
Performed end-to-end ETL, exploratory data analysis, and categorical feature encoding on structured behavioral data.
Applied GridSearchCV for hyperparameter tuning to generate actionable insights for targeting high-intent customers.
April 10, 2025
Google Analytics CAPSTONE Project
Built, tuned, and evaluated multiple classification models (Logistic Regression, Random Forest) with hyperparameter optimization using GridSearchCV;
translated outputs into HR strategy recommendations...
Developed a machine learning model to help HR teams identify employees likely to leave, using Random Forest with 96% recall.
Conducted exploratory data analysis, feature engineering, and model tuning to generate actionable retention insights from a dataset of 14,999 employees.
March 28, 2025
Google Analytics Case Study
Analyzed behavioral signals, engineered features, and used logistic regression, random forest, and
XGBoost to identify at-risk users and recommend data-driven retention strategies...
Built and evaluated churn prediction models using behavioral data from Waze users.
Improved recall from 7% to 38% using XGBoost and delivered strategic recommendations focused on early user engagement.
November 2, 2024
Google Analytics CAPSTONE
This project outlines the structured approach used in my Bellabeat Case Study
(a Capstone project as a part of my Google Data Analytics: Proffesional Certificate), following phases: Ask, Prepare, Process, Analyze, Share, and Act.
