Hussein Jawad
Hussein Jawad is a Senior Data Scientist specializing in NLP, holding degrees from École Polytechnique and Télécom Paris. Based in Paris, he possesses a foundation in programming, statistical modeling, and MLOps.
Currently, he works on the development team of MAPIE while delivering innovative solutions at Capgemini Invent. With publications on LLM security and achievements in global competitions, he combines technical expertise with cross-functional collaboration.
Sessions
MAPIE (Model Agnostic Prediction Interval Estimator) is your go-to solution for managing uncertainties and risks in machine learning models. This Python library, nestled within scikit-learn-contrib, offers a way to calculate prediction sets with controlled coverage rates for regression and classification tasks.
But it doesn't stop there - MAPIE can also be used to handle more complex tasks like time series analysis, multi-label classification, computer vision and natural language processing, ensuring probabilistic guarantees on crucial metrics.
Join us as we delve into the world of conformal predictions and how to quickly manage your uncertainties using MAPIE.