SATHVIK
SHETTY

I'm a final-year Computer Science engineer who works across the full spectrum of applied AI — classical machine learning, deep learning, and large language models — rather than staying in one lane. I've trained and evaluated traditional ML models (regression, classification, clustering, dimensionality reduction), built neural architectures from first principles, and shipped LLM-based systems end-to-end, from retrieval and agent orchestration to production deployment.

What ties it together is a research mindset: I learn by building and measuring, not by stopping at a tutorial. I care less about which model or technique is newest and more about whether a system can be trusted to do what it claims — which is why evaluation, experimentation, and rigorous data analysis show up everywhere in how I work, whether that's a case study, a classical ML pipeline, or an LLM application.