
Aspiring Data Scientist with hands-on AIML internship experience at Quadsync Tech Solutions, collaborating with cross-functional teams to build, evaluate, and deploy predictive models. Skilled in Python, scikit-learn, and Flask/Streamlit, with a track record of cleaning real-world datasets, comparing multiple regression and classification models with cross-validation, and shipping production-ready interfaces on Vercel and Render. Building foundational expertise in Generative Al and LLM engineering through a structured Simplilearn certification program, with a focus on turning raw data into reliable, user-facing predictions.
Programming Languages & Core : Python, SQL
Machine Learning & Deep Learning : scikit-learn, Regression, Classification, Random Forest, XGBoost, SVM, Neural Networks, Generative Al
Frameworks & Libraries : Flask, Streamlit, Pandas, NumPy
Tools & Deployment : Git, GitHub, Vercel, Render, Docker