Building an Adaptive Learning System using Bayesian Modelling in Python

This repository contains the materials used in the presentation at the PyCon HK 2015 (http://2015.pycon.hk/). The presentation introduces how to implement an adaptive learning system using Bayesian modelling in Python.

Tools Introduced

• PyMC: https://github.com/pymc-devs/pymc

Adaptive Learning in Action

Our "Learn Katakana" App makes use of Bayesian modelling to help users to learn Japanese Katakana effectively. It is freely available on both Android and iOS:

• Android: https://play.google.com/store/apps/details?id=com.axonlabs.katakana
• iOS: https://itunes.apple.com/hk/app/learn-katakana-xue-xi-pian/id1018124358?mt=8

References

• Probabilistic Programming and Bayesian Methods for Hackers https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
• Adaptive Learning: https://en.wikipedia.org/wiki/Adaptive_learning
• Item Response Theory: https://en.wikipedia.org/wiki/Item_response_theory