I have built several data‑driven and AI‑powered projects that showcase my abilities in analytics, machine learning, web scraping, and full‑stack development. These projects complement the internships listed on linkedin experience and demonstrate end‑to‑end delivery from data ingestion to user‑facing interfaces.
BlinkIT Sales Analysis Dashboard – Power BI (Aug 2026). Analyzed BlinkIT sales data using Power BI to understand sales performance and identify key business insights. • Cleaned and transformed the dataset using Power Query. • Created DAX measures and KPIs to analyze total sales, average sales, ratings, and outlet performance. • Built an interactive dashboard with cards, charts, slicers, and filters. • Analyzed sales based on outlet type, location, item category, and other business factors. • Designed the dashboard to make sales trends and performance easier to understand.
Credit Card Approval Prediction Using Machine Learning (Mar 2025). Developed a credit‑card approval prediction system that leverages machine learning to automate and enhance the approval process. ✅ Data Preprocessing: handling missing values, encoding categorical features, scaling numeric data. ✅ Imbalanced Data Handling: using SMOTE. ✅ Model Training & Evaluation: Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, XGBoost. ✅ Fairness & Bias Analysis across demographic groups. ✅ Interactive Prediction Feature for real‑time credit‑approval probability.
Tech Job Portal (Feb 2025). Built an AI‑powered job portal that scrapes listings from Indeed, Glassdoor, etc., and provides personalized job recommendations with real‑time email/SMS alerts. Features include automated scraping (Python, BeautifulSoup, Scrapy), AI‑driven recommendation engine, user authentication, search filters, job bookmarking, and a full‑stack front‑end (React.js/Vue.js) with a Django/Flask back‑end.
Amazon Scraper (Jan 2025). Created a web scraper using Python, BeautifulSoup, and Scrapy to extract Amazon product details (price, ratings, reviews, availability) for price monitoring, competitor analysis, and market research.
Indeed Scraper (Jan 2025). Developed a scraper with Python, BeautifulSoup, and Scrapy to collect Indeed job listings (titles, companies, locations, salaries, descriptions) for job‑market analysis, trend tracking, and automated job‑alert generation.
Fake News Detection (May 2024). Built a machine‑learning/NLP system using Python, Scikit‑learn, TensorFlow, and NLTK on the LIAR and FakeNewsNet datasets to classify news as real or fake, performing text analysis to detect misleading patterns and promote reliable information.