Pavan Konjeti

ACADEMIC PROJECTS 1. Developed 85% accurate ANN model in Python (TensorFlow, NumPy, Pandas, Scikit-learn) for bank customer churn prediction. 2. Implemented machine learning techniques (multiple regression, classification, clustering) in Python to estimate sales, classify fraud and late delivery risk, and identify customer segments. 2. Built SQL database (Boyce-Codd normalized) for efficient management of sporting events. 3. Predicted telecom churn using Logistic Regression, Random Forests, and KNN in R. 4. Managed vehicle fleet & assets with low-code apps (Appian) for service, sales, renting & maintenance. 5. Automated tuition estimate emails with web scraping & data processing using UiPath.