Lecture

Deep Knowledge Tracing

Description

This lecture delves into Deep Knowledge Tracing, a model for predicting student learning. It covers the concepts of Recurrent Neural Networks, Hidden Layers, and the Binary Crossentropy Loss function. The instructor discusses the application of AFM, PFA, BKT, and DKT models on educational data, emphasizing the importance of visualizing and comparing their performance.

Official source

https://mediaspace.epfl.ch/media/0_yvmz18om

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Ontological neighbourhood

Information engineering

Machine learning: Artificial neural networks

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