Knowledge Tracing: Student Learning and Latent Variables

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Surprise, Curiosity and Reward: An Evolutionary Perspective

Explores the evolutionary perspective on surprise, curiosity, and reward, focusing on the role of primary and secondary reward signals.

Visual Extensions in the Workplace

Explores the use of visual extensions, such as virtual reality and augmented reality, in enhancing workplace efficiency and communication.

Latent variables in choice models: Optima case study

Explores the Optima case study, analyzing attitudes and mode choice.

Textual Data Analysis: Classification & Dimensionality Reduction

Explores textual data classification, focusing on methods like Naive Bayes and dimensionality reduction techniques like Principal Component Analysis.

Introduction to Machine Learning: Course Overview and Basics

Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.

Introduction to Mechanical Design: Course Overview and Objectives

Introduces the Mechanical Design course, covering its structure, objectives, and evaluation methods.

Air Pollution Data Analysis

Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.

Topic Models: Understanding Latent Structures

Explores topic models, Gaussian mixture models, Latent Dirichlet Allocation, and variational inference in understanding latent structures within data.

Behavioural Control in Animals and Robots

Explores controlling behavior in animals and robots, covering historical perspectives, neuron activation, Drosophila model, advanced techniques, and mini-project organization.

Knowledge Tracing

Delves into Bayesian Knowledge Tracing and Learning Curves, exploring the prediction of student knowledge over time and the importance of accurate performance measurement.