Data Science intern
- Built a streamlit web app to predict calories burnt using machine learning
- Trained models with Scikit-learn and evaluated them with R² score


Highly motivated Data Scientist with a strong background in machine learning, data analysis, and predictive modeling. Developed and deployed models for food price prediction and calorie estimation. Skilled in data preprocessing, feature engineering, and model evaluation, with expertise in SQL and Power BI for insightful data visualization. Passionate about leveraging data driven solutions to solve complex problems and drive business decisions, while continuously improving my technical skills.
Programming & Tools: Python, SQL, Git, GitHub
Machine Learning: Scikit-learn, XGBoost, Random Forest, Linear Regression, Feature Engineering
Data Visualization: Power BI, Matplotlib, Seaborn
Deployment & Others: Streamlit, Pickle, Joblib
Soft Skills: Problem solving, teamwork, time management