Onkar Gorule

I’m an Assistant Professor experienced in statistics and machine learning, focused on extracting valuable insights from complex datasets and making data-driven decisions. I simplify topics like Statistics and Machine Learning through structured curriculum delivery, while staying hands-on with real-world solutions using Python. In an industry internship, I built an NLP-based chatbot with Flask and developed a Sign Language Detection system using Python and OpenCV with a 94% accuracy rate.

My work blends rigorous statistical analysis with practical ML engineering: I created a Streamlit-based automated data analysis web application featuring EDA, visualization, and statistical hypothesis testing (t-test, ANOVA, Chi-Square), plus model evaluation using R², MSE, and RMSE. I also developed a leukemia image classification pipeline using VGG16 and YOLOv8, and an insurance price prediction model achieving 84.6% variance capture with Gradient Boosting Regressor—always aiming for accurate interpretation and measurable business impact.