🚀 About Me

🎓 Pursuing B.E. Computer Science and Engineering (AI & ML) at Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai.

🤖 Passionate about Machine Learning, Generative AI, Natural Language Processing, and building practical AI-driven applications.

🛠️ Experienced in the complete machine learning lifecycle—from data preprocessing and model development to API integration, cloud deployment, and full-stack implementation.

🏆 Recipient of the Innovation Excellence Award 2025 for developing an AI-powered House Price Prediction platform.

💡 Interested in transforming complex datasets into scalable, user-friendly solutions that deliver real-world impact.

• Python
• JavaScript
• C

• HTML5
• CSS3
• Tailwind CSS
• React
• FastAPI (REST APIs)

• Regression & Classification
• XGBoost
• NLP (Natural Language Processing)
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• LangChain
• Transformers
• Flan-T5
• Hugging Face Ecosystem

• Pandas
• NumPy
• Scikit-learn
• Matplotlib
• Seaborn
• Streamlit

• PostgreSQL
• MySQL
• Git
• GitHub
• Linux
• Render
• Neon Serverless

A full-stack machine learning platform that predicts residential property prices across Tamil Nadu districts using location and housing attributes.

• Built with React, FastAPI, PostgreSQL (Neon Serverless), and Render
• Real-time house price prediction using a deployed ML model
• District and taluk-level housing interest analytics
• Botpress-powered virtual assistant for user guidance
• Open-source model and dataset hosted on Hugging Face
• End-to-end deployment covering frontend, backend, database, and ML serving

An AI conversational platform for exploring oceanographic ARGO float data through natural language interactions.

• Natural language querying using LLMs and RAG
• Vector-based semantic search
• Interactive maps and time-series visualizations using Streamlit
• Built as part of the Smart India Hackathon (SIH)

An AI-powered document processing and information extraction system.

• Developed using Python, Streamlit, and EasyOCR
• Automated document classification for invoices, contracts, forms, and identity documents
• Extracted entities such as names, invoice numbers, dates, and monetary values
• Implemented sensitive data masking for Aadhaar numbers, phone numbers, and email addresses
• Designed analytics dashboard and CSV export functionality for processed records

• NPTEL – Introduction to Machine Learning
• 🏆 Innovation Excellence Award 2025 (AICTE–IDEA Lab Initiative)
• Smart India Hackathon (SIH) Participant

• LinkedIn: www.linkedin.com/in/gauthaman-v-414a9831a
• GitHub: https://github.com/runeking2006

"Build systems that solve real problems — learning follows naturally."