I build applied machine learning systems end-to-end — not just training a model in a notebook, but taking it from raw data through to something that's actually deployed and usable.
Currently a CS undergrad, spending most of my time in the space between ML research and backend engineering.
Stack
Projects
hybrid-ids-nsl-kdd
Hybrid intrusion detection system trained on the NSL-KDD dataset.
eye-disease-predictor
CNN-based classifier for detecting eye disease from retinal images.
dynamic-ride-pricing
ML-driven dynamic pricing model for ride-hailing, reacting to demand in real time.
customer-churn
End-to-end churn prediction pipeline, feature engineering through deployment.
house-price-prediction
Regression pipeline estimating house prices from structured data.
Infer-Labs 
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