Projects¶

Welcome to my project portfolio! Here you'll find a curated selection of my best work, spanning data engineering, automation, web development, and more. Explore featured highlights or browse the full list below.

🚀 Featured Projects¶

GSTN Hackathon: Predictive Binary Classification

Robust, interpretable ML pipeline for binary classification on anonymized GSTN data. Achieved >97% accuracy, strong F1/MCC, and strict compliance with competition rules. Python, scikit-learn, XGBoost/LightGBM, SHAP, and reproducibility scripts.

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Examination Management System DB

Robust, production-ready database system for managing exams, students, proctoring, and results. Multi-RDBMS support (SQLite, MySQL, PostgreSQL), Python automation, Dockerized environments, and automated testing.

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S3 Faker

Fake data generator with AWS S3 (LocalStack) integration. Generates large datasets using Python & Faker, supports CSV/JSON/Parquet, and automates uploads for testing cloud pipelines.

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Paraxcel

Python toolkit for advanced Excel data extraction, transformation, and visualization. Built with Pandas, Openpyxl, Matplotlib, and Seaborn for seamless spreadsheet analytics.

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Naukri Webscraper

Selenium-powered Python tool to automate job search and data extraction from Naukri.com. Features skill-based filtering, CSV export, and robust automated testing with pytest.

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Test Management Site

Dynamic, responsive web app for test creation, execution, and result tracking. Built with vanilla JS, HTML, CSS, Bootstrap, and localStorage for a seamless frontend experience.

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📚 All Projects¶

LatestA–Z

Examination Management System DB

Multi-RDBMS exam/test management, automation, Docker, Python, CI-ready.
S3 Faker

Fake data generator with S3/LocalStack integration for cloud testing.
Paraxcel

Excel data extraction, transformation, and visualization toolkit.
Naukri Webscraper

Automated job scraping, filtering, and CSV export from Naukri.com.
Test Management Site

Frontend web app for test management and result tracking.
GSTN Hackathon: Predictive Binary Classification

Robust, interpretable ML pipeline for binary classification on anonymized GSTN data. >97% accuracy, strong F1/MCC, reproducibility, and compliance.

🌟 Why These Projects?¶

Each featured project demonstrates a unique blend of technical depth, problem-solving, and real-world impact—from scalable database design and cloud automation to advanced data analytics and modern web development.
Explore the detailed write-ups for code samples, visuals, and outcomes.