Talk: Building an Adaptive Learning System using Bayesian Modelling in Python

Speaker: Albert Au Yeung (Albert)

Company: Axon Labs Limited

Language: English (with English Slides)

Slides: Building an Adaptive Learning System using Bayesian Modelling in Python (CC-BY)

Photo of Albert Au Yeung

About Speaker

Albert Au Yeung is a co-founder and CTO of Axon Labs Limited, a Hong Kong-based technology company focusing on mobile app development, data mining, machine learning and applied cognitive psychology. Albert has a PhD in Computer Science and has been conducting research on social network analysis, natural language processing, data mining and machine learning. He has been using Python for conducting experiments, processing data and developing applications for over 10 years.

About the Topic

Adaptive learning is a method of education that uses computers to present teaching materials according to the specific needs of individual learners. A common method of implementing adaptive learning is to use Bayesian models. In this talk, I will present a brief introduction of adaptive learning and bayesian modelling, and will give a tutorial on how to use different tools in Python, including PyMC, NumPy and SciPy, to implement an adaptive learning system for presenting teaching materials and to learners according to our estimation of their individual abilities. We will use a mobile app for learning Japanese characters as an example to illustrate how Python can be used to implement such a system.