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In this hands-on session, we’ll discover the often overlooked but essential topic of model calibration in machine learning.
You will explore what it means for a model to be calibrated, why it matters in real-world applications, and how to evaluate and improve calibration using practical tools and techniques.
Through collaborative coding and experimentation, we’ll compare calibrated and non-calibrated models to see the impact on decision-making and performance.