Knowledge Tracing

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Related lectures (28)

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Explores Variational Auto-Encoders, Bayesian inference, attention-based latent spaces, and the effectiveness of Transformers in language processing.

Music Semantics: Problems and Prospects

Explores music semantics, discussing inferences triggered by different musical elements and proposing a framework for understanding music's meaning.

Maximum Likelihood: Inference and Model Comparison

Explores maximum likelihood inference, model selection, and comparing models using likelihood ratios.

Knowledge Inference: Entity Disambiguation and Graph Embeddings

Explores entity disambiguation, graph embeddings, scoring functions, and learning methods.

Knowledge Tracing: Student Learning and Latent Variables

Explores Bayesian Knowledge Tracing and latent variables for tracing student knowledge and making predictions.

Inference of Reaction Kinetics

Focuses on the inference of reaction kinetics in combustion, covering rules inference, sensitivity analysis, and Bayesian inference.

Decision Trees and CLT's: Inference and Machine Learning

Explores decision trees, ensembles, CLT, inference, machine learning, diagnostic methods, boosting, and variance estimation.

Propositional Logic: Inference Rules

Covers the interpretation of propositional logic and inference rules for implication, conjunction, and double negation.

Data Science Visualization with Pandas

Covers data manipulation and exploration using Python with a focus on visualization techniques.

Topic Models: Latent Dirichlet Allocation

Covers topic models, focusing on Latent Dirichlet Allocation, clustering, GMMs, Dirichlet distribution, LDA learning, and applications in digital humanities.