Swetha Kalakoti

• Developed a machine learning application to predict flight delays using historical flight, weather, and scheduling data. • Performed data preprocessing, feature engineering, and exploratory data analysis to improve prediction accuracy. • Implemented Logistic Regression, Decision Tree, and Random Forest algorithms using Scikit-learn. • Strengthened understanding of machine learning workflows, data preprocessing, and model evaluation. • Technologies: Python, Pandas, NumPy, Matplotlib, Scikit-learn.

Developed a scholarship recommendation system using FastAPI and Streamlit. • Built REST APIs to filter scholarships based on student eligibility. • Designed an interactive user interface for easy scholarship search. • Integrated frontend and backend for real-time data retrieval. • Improved application development and API integration skills.

Developed a fraud detection system using PySpark on Azure Databricks. • Processed and analyzed large-scale financial transaction datasets. • Built machine learning models using Spark MLlib and Scikit-learn. • Utilized MLflow for model tracking and performance monitoring. • Applied big data processing techniques for accurate fraud detection.