Data Scientist with 4 years of hands-on experience building data-driven solutions and a background as a Data Science student active on GitHub. Pragmatic and curious, they bridge academic foundations with practical applied work, focusing on turning noisy data into actionable insights. Comfortable with the full data workflow from preprocessing and modeling to evaluation and communication, they prioritize reproducible analyses. Though early in their career, they demonstrate strong learning momentum and a collaborative mindset that accelerates team impact.
Detecting silent model failure. NannyML estimates performance with an algorithm called Confidence-based Performance estimation (CBPE), developed by core contributors. It is the only open-source algorithm capable of fully capturing the impact of data drift on performance.
TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
Contributions:6 reviews, 1 branch, 1 comment in 5 months
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