🚀 AI Engineer | Machine Learning Engineer | Data Scientist

🎯 Mission

Building production-grade AI/ML solutions that solve real-world problems. Specializing in Generative AI, Large Language Models, Predictive Analytics, and Autonomous AI Agents.

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💼 Core Expertise

🤖 AI & Machine Learning

• Generative AI & LLMs: LangChain, LangGraph, Prompt Engineering, RAG Systems, Fine-tuning (LoRA, QLoRA)
• Agentic AI: Multi-agent systems, Tool calling, Reasoning chains, Model Context Protocol (MCP)
• Deep Learning: TensorFlow, PyTorch, Keras, Custom architectures
• Classical ML: Scikit-learn, XGBoost, Random Forests, Ensemble methods

📊 Data Science & Analytics

• Feature Engineering: Statistical analysis, Dimensionality reduction, Feature selection
• Model Optimization: Hyperparameter tuning, Cross-validation, SHAP analysis
• Time Series: ARIMA, Prophet, LSTM for forecasting
• Data Pipeline: ETL, Data warehousing, Big Data processing

🔧 Production & Deployment

• API Development: FastAPI, Flask, Django
• ML Operations: MLflow tracking, Model versioning, A/B testing
• Cloud & DevOps: Docker, GitHub Actions, CI/CD pipelines
• Databases: PostgreSQL, MySQL, Redis, Supabase, Vector DBs

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🌟 Pinned Projects

📈 Credit Card Risk Modelling | ML Production System

• Built end-to-end ML pipeline for credit default prediction
• Tech: Scikit-learn, XGBoost, Feature Engineering, Streamlit deployment
• Impact: Predictive model with 89% AUC on unseen data
• Website

🏥 Healthcare Premium Prediction | Regression ML

• ML model for predicting insurance premium rates
• Tech: Pandas, NumPy, Scikit-learn, Statistical modeling
• Demonstrates feature engineering for healthcare domain
• Website

🤓 LearnLock | AI-Powered Learning Engine

• Adversarial learning system using LLM as knowledge validator
• Tech: LangChain, OpenAI API, Vector embeddings, FastAPI
• Validates understanding through contradiction detection & spaced repetition
• Try Live Demo | PyPI Package

🏘️ Real Estate Sentiment Tracker | NLP + Data Analytics

• Sentiment analysis on real estate market trends
• Tech: NLTK, Pandas, Web scraping, Visualization
• GitHub Repository

📄 Paper | ML Research Implementation

• Research paper implementation project exploring machine learning algorithms
• Tech: Python, Scikit-learn, NumPy, Data Processing Pipelines
• Focus: Implementing theoretical concepts from academic papers
• GitHub Repository

🔧 DamageX | Computer Vision & ML

• Damage assessment platform using computer vision and deep learning
• Tech: TypeScript, PyTorch, CNN, Image Processing
• Impact: 91% accuracy in damage detection
• Website

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📚 Tech Stack

🐍 Languages: Python 3.9+, SQL, R (basic)
🤖 AI/LLMs: OpenAI, LangChain, LangGraph, Hugging Face, Groq
📊 ML Libraries: TensorFlow, PyTorch, Scikit-learn, XGBoost, Keras
📈 Data: Pandas, NumPy, SciPy, Matplotlib, Seaborn, Plotly
🗄️ Databases: PostgreSQL, MySQL, Redis, Supabase, Vector DBs (Pinecone, ChromaDB)
⚙️ Production: FastAPI, Flask, Django, Streamlit, Docker
☁️ DevOps: GitHub Actions, Git, MLflow, Hugging Face Hub

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📈 Stats & Contributions

• 532+ GitHub contributions in 2024 | Learning in public approach
• 50+ ML/AI projects across data science, deep learning, and generative AI
• Open-source contributor with published packages
• Hackathon builder - Developed multiple AI solutions in competitive environments

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