🎯 Full Stack Developer | AI/ML Enthusiast | LLM Explorer
🔧 Working with MERN & PERN | 🤖 Learning Chatbots, Deep Learning, LangChain & Vector DBs
📍 Based in India | 🧠 Passionate about building with code & curiosity
- Frontend: React.js, Redux Toolkit, TypeScript, CSS, ShadCN/UI
- Backend: Node.js, Express.js, PostgreSQL, MongoDB, REST APIs, JWT Auth
- Dev Tools: Git, GitHub, Postman, Docker, Vercel, Render, Railway
- ML Libraries: Scikit-learn, XGBoost, Pandas, NumPy, Matplotlib, Seaborn
- Deep Learning: PyTorch (in progress), TensorFlow (beginner)
- Chatbots & LLMs: LangChain, OpenAI API, RAG, Prompt Engineering
- Vector DBs: Chroma, Pinecone, FAISS (learning)
A feature-rich accounting system inspired by Tally ERP
Stack: MERN (MongoDB, Express, React, Node.js)
Features: Ledger, Invoicing, Multi-user Auth, Role-based Access
🔗 GitHub Repo | 🌐 Live Demo
Real-time audio & video collaboration platform with recording support
Stack: React, Web Audio API, Node.js, PostgreSQL, Socket.io
Features: Media sync, Real-time latency diagnostics, Recording
🔗 GitHub Repo | 🌐 Live Demo
Congestion prediction & visualization using ML and time series forecasting
Stack: LSTM, Facebook Prophet, Flask, Google Maps API, Kepler.gl
Features: Predictive congestion mapping, Peak hour analytics
🔗 GitHub Repo | 🌐 Live Demo
Chatbot prototype using RAG pipeline for intelligent Q&A from documents
Stack: Python, LangChain, ChromaDB, Streamlit, OpenAI API
Features: Document ingestion, Vector search, Semantic chat
🔗 GitHub Repo | 🌐 Live Demo
A workspace for fine-tuning, prompt engineering, and deploying small LLMs
Stack: PyTorch, Hugging Face Transformers, Gradio/Streamlit
Features: Custom prompts, Dataset uploads, Output tuning
🔗 GitHub Repo | 🌐 Live Demo
- TypeScript & Advanced React Patterns
- Deep Learning with PyTorch
- LangChain for RAG pipelines
- Vector DBs: Chroma, FAISS, Pinecone
- MLOps with DVC, MLflow, Hugging Face Hub
- Building and fine-tuning LLMs
"From REST to RAG, I build, learn, and iterate." – Aziz Officewala