Work

Projects

A collection of open-source tools, experiments, and production systems I've built or contributed to.

RAG · NLP

RAGineer

Production-ready local RAG Text-to-SQL chatbot that converts natural language into safe PostgreSQL queries with 84% SQL accuracy.

pythonpostgresqlollamachromadb+1
  • 84% SQL accuracy, 80% end-to-end, ~2.5s latency
  • SQL injection prevention, rate limiting, 64 tests at 97% coverage
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MLOps · Production

Real-Time Fraud Detection

High-performance FastAPI microservice achieving 90% latency reduction (50ms → 5.4ms) with full production observability.

pythonfastapixgboostdocker+1
  • False Positive precision from 6% → 78%, 83% Recall maintained
  • MLflow experiment tracking, class-weighted XGBoost
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RAG · GenAI

GetAnime

RAG-powered semantic anime recommendation engine with sub-second latency and 95% relevance accuracy across 12,000+ entries.

langchaingroqchromadbdocker+1
  • Sub-second query latency with Groq LLM + ChromaDB
  • 99.5% uptime on GCP with Kubernetes + Grafana monitoring
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Healthcare · DL

Mental Health Predictor

AI-driven tool predicting depression among students using TensorFlow, trained on 27,000 records with LIME interpretability.

tensorflowstreamlitlimegemini-ai
  • Neural network on 27,000 student records
  • LIME interpretability for transparent predictions
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Data Science

Data Analysis Toolkit

Interactive toolkit for EDA, feature engineering, model building, and visualization with Plotly and scikit-learn.

pythonstreamlitplotlyscikit-learn
  • End-to-end: cleaning → feature engineering → model training
  • Interactive Plotly visualizations
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NLP · MLOps

E2E Text Summarization

Production-ready NLP summarization pipeline with CI/CD, Docker, and AWS EC2/ECR deployment.

transformersfastapidockeraws+1
  • CI/CD with GitHub Actions, Dockerized deployment
  • AWS EC2 hosting + ECR image registry
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Healthcare · ML

Heart Disease Prediction

ML-based heart disease risk assessment comparing Logistic Regression, Random Forest, Gradient Boosting, and SVM.

pythonscikit-learnstreamlitmatplotlib
  • 85.2% test accuracy with Logistic Regression
  • Interactive Streamlit web application
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Web Dev

Note Taking App

Full-stack Django note management app with authentication, rich text editing, search, and collaboration tools.

djangosqlbootstrapjavascript
  • User authentication and note CRUD
  • Search, filtering, and file uploads
Read more →