For my Digital Payment & Financial Transaction Analytics project, I analyzed more than 1.04 million transaction records using Python, Pandas, and NumPy. I cleaned and explored the data, identifying duplicates, repeated transaction IDs, and account-name inconsistencies.
I developed SQL queries to examine transaction patterns and designed a three-page interactive Power BI dashboard with KPI metrics, transaction trends, and high-value transaction monitoring.
As a Machine Learning Intern at Techqkonnect, I analyzed datasets and processed structured data for model input. I also built and deployed web applications using Flask and Streamlit, and increased image-recognition model accuracy by 15% through iterative analysis and tuning.

