I am a machine learning enthusiast focused on building practical AI systems using Python.
Currently preparing for Google Summer of Code and contributing to the neural-lam project by improving documentation and developer accessibility through automated documentation generation.
My work and learning focus on:
- Machine learning systems and recommendation models
- Python-based AI applications
- Model deployment and engineering workflows
- Open source collaboration
An ML-powered web app that predicts possible diseases from user symptoms and offers recommendations.
Tech: Python, Scikit-learn, Flask
What I learned: End-to-end ML deployment, handling user input, building simple REST APIs.
A personalized book recommender using collaborative filtering and cosine similarity.
Tech: Python, Pandas, Scikit-learn
What I learned: Data preprocessing, similarity metrics, evaluating recommender systems.
- Open Source Contributions – Especially in AI/ML projects (I'm preparing for GSoC 2026 with the mllam/neural-lam project!)
- Collaborations on real-world AI applications, ML systems, and agentic AI.
- Mentorship in ML system design and large-scale deployments.