Pooja Bommashettihalli Rangadhamaiah

A Data Science Master’s student with a strong foundation in data science technologies, passionate about extracting insights from data to drive impactful solutions. With experience in resolving technical challenges, I bring a problem-solving mindset to both independent and collaborative projects. Eager to explore AI and predictive analytics, I am committed to continuous learning and applying data-driven techniques to real-world problems.

Spam Detector 

• Developed a machine learning model to classify emails as spam or legitimate, improving email security and filtering efficiency.
• Implemented Naïve Bayes classification and keyword-based feature extraction to detect spam with high accuracy.
• Automated the process of filtering spam emails, reducing manual effort and enhancing user experience.

SuperSense – ML Assistance for the Deaf and Dumb 

• Developed a computer vision-based application that recognizes and translates American Sign Language (ASL) hand gestures into text and speech.
• Implemented a Convolutional Neural Network (CNN) model trained on ASL hand signs, enabling real-time gesture detection via a webcam.
• Enhanced accessibility by bridging the communication gap between the deaf and dumb and the general public through automated sign language translation.

 Pymon Game

• Developed a Python-based virtual pet game using Object-Oriented Programming (OOP), featuring an interactive battle system.
• Implemented file handling to dynamically read and update game data, ensuring adaptability with different datasets.
• Designed a map-based exploration system where players navigate, capture creatures, and manage energy levels to win.

COVID-19 Vaccination Database

• Designed and implemented an SQL-based relational database to store and manage vaccination data efficiently.
• Optimized data retrieval and querying for insights on vaccination trends and distribution.
• Ensured data integrity and scalability, enabling effective analysis and visualization.