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Probabilistic ML - Lecture 16 - Graphical Models
MLVU 4.2: Class imbalance and feature design
11 Sequential Data: Markov Models, Word Embeddings and LSTMs
Lecture 112: Production Megakernels for Real-World Inference
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Last Updated: October 1, 2026
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Summary
Virginia Tech Machine Learning. This is the sixteenth lecture in the Probabilistic ML class of Prof. Dr. Philipp Hennig in the Summer Term 2020 at the University of ... Continuing our theme of pre-processing, we discuss how to deal with class imbalance, how to transform given data to features, ... Joe Fioti explains how the Luminal compiler brings megakernels into production inference alongside traditional kernel