I build end-to-end Machine Learning applications by taking models beyond experimentation into APIs, deployment-ready applications, and real-world software solutions.
- 🤖 Passionate about Machine Learning, Deep Learning, and AI Engineering
- 🚀 Building end-to-end ML applications with Python, FastAPI, and Flask
- 📊 Experienced in Computer Vision, Recommendation Systems, Network Security, and Model Monitoring projects
- 📚 Continuously learning Software Engineering, MLOps Fundamentals, and LLM Applications
- 🎯 Open to Machine Learning Engineer, AI Engineer, and Data Scientist opportunities
Python
TensorFlow • NumPy • Pandas • Scikit-learn
FastAPI • Flask
MySQL • PostgreSQL • SQLite
Git • GitHub
End-to-end Machine Learning application for detecting malicious network traffic using anomaly detection techniques. Includes a Flask dashboard, SQLite logging, and interactive visualizations.
Tech Stack: Python • Scikit-learn • Flask • SQLite • Plotly
Deep Learning application for retinal disease classification using TensorFlow with image preprocessing, model evaluation, and prediction pipeline.
Tech Stack: TensorFlow • Flask • OpenCV • NumPy
Recommendation engine that suggests restaurants using content-based filtering with an API for fast and scalable recommendations.
Tech Stack: Python • Scikit-learn • FastAPI • Pandas
- Machine Learning Engineering
- MLOps Fundamentals
- LLM Applications
- Retrieval-Augmented Generation (RAG)
- Software Engineering Best Practices
⭐ Thanks for visiting my profile! Feel free to explore my repositories and connect with me.