AI / ML
Movie Recommendation System
Personalized movie recommendations powered by machine learning and user preference analysis.
I'm
I’m a Computer Science undergraduate focused on
building real-world AI systems—not just models, but end-to-end applications that work
beyond experimentation.
My work spans machine learning, generative AI, and backend systems.
I’ve built ML pipelines for prediction tasks, developed LLM-based applications using
APIs, and designed backend architectures to integrate AI into usable products. I’m
particularly interested in how systems behave in production—where models fail, scale,
and interact with real users.
Alongside AI, I have a worked on with backend and full-stack
development, working with Node.js, Express, Next.js, and relational
databases to build structured and maintainable systems.
Currently, I’m exploring LLMs, prompt engineering, and production-oriented AI
workflows, with a focus on building systems that are not just intelligent,
but reliable and scalable.
I prefer learning by building, testing, and iterating—and I’m looking to contribute to
teams working on real AI problems.
Python & Machine Learning
Intermediate
Generative AI / LLM APIs
Intermediate
Databases (MySQL, PostgreSQL)
Intermediate
Data Structures & Algorithms
Intermediate
Pursuing B.Tech in Computer Science Engineering (CSE)
Self-motivated to take personal chess lessons, improving my analytical and strategic thinking. Gained valuable skills in game strategy and problem-solving through independent practice.
AI / ML
Personalized movie recommendations powered by machine learning and user preference analysis.
Retrieval-Augmented Generation chatbot that answers queries using custom knowledge sources.
FULL STACK
Collaborative productivity platform for note-taking, task management, and team workflows.
Collection of machine learning models, experiments, and data-driven problem-solving implementations.