Dinesh Polamarasetti

I am a computer science undergraduate with hands-on experience building and deploying machine learning models and mobile applications. I developed Random Forest regression models for CO/CO2 prediction that achieved over 90% accuracy, processed and cleaned tens of thousands of data points, and improved model error through hyperparameter tuning.

I have internship experience in ML and Android development, where I conducted extensive testing, reported critical bugs, and improved app performance by reducing load times. I also built a FinBERT-based sentiment analysis pipeline that processed 50,000+ financial articles and reached 85% classification accuracy to support investment insights.

I bring practical skills in Python, SQL, C, Android (Kotlin), and data engineering concepts, supported by certifications in machine learning and data analysis. I am motivated to join a team where I can apply data-driven modeling and software development to solve real-world problems and continue growing technically.