BTech undergraduate with a minor in AI & ML with hands-on experience in machine learning, Power BI dashboards, and data analysis; seeking Data Analyst or Data Science internship roles.
Completed intensive training in Data Science, EDA, Power BI, and Machine Learning., Cleaned and analyzed 40K+ records to improve data accuracy and usability.Built interactive Power BI dashboards with DAX measures, KPIs, filters, and slicers.Developed and deployed a Movie Recommendation System using content-based filtering with Streamlit.
Completed intensive training in Data Science, EDA, Power BI, and Machine Learning.
Cleaned and analyzed 40K+ records to improve data accuracy and usability.
Built interactive Power BI dashboards with DAX measures, KPIs, filters, and slicers.
Developed and deployed a Movie Recommendation System using content-based filtering with Streamlit.
Built interactive Power BI dashboard, Evaluated 50K+ sales records to track revenue, profit, and growth. Created 8+ KPIs using DAX, slicers, and drill-downs.
Reviewed 100K+ transactions to identify spending patterns, fraud-related indicators using DAX and data modeling to deliver insights for financial analysis.
Created a regression-based sales prediction model using historical sales and product data. Handled missing values, categorical encoding, and outliers; trained models such as Linear Regression and Gradient Boosting. Analyzed sales trends to support business decision-making.
Trained churn prediction models using Logistic Regression, Random Forest, XGBoost. Performed EDA and feature engineering; evaluated models using F1-score and recall.Achieved ~95% accuracy.
Built a content-based recommendation engine using Python and Scikit-learn.Performed feature extraction and cosine similarity analysis.Deployed the application using Streamlit for real-time recommendation.
Designed an interactive dashboard to track KPIs and performance metrics using data cleaning, calculations for actionable insights for 30K+ records.Created KPIs using DAX, slicers, and drill-downs.
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