Demos for Computational Cognitive Science

By Suhas Arehalli, Tom McCoy, Hongru Zhu, and Tal Linzen

These resources were created with funding from a Johns Hopkins University Center for Educational Resources Technology Fellows Grant. You may use any of these resources for educational purposes. Although you do not have to contact us to use anything here, we would love to hear it if you have found these demos and homeworks useful!

Basics

Introduction to probability with dice by Tom McCoy

 

Introduction to Python: Modeling phonological stress assignment by Tom McCoy

Bayesian modeling

Bayesian modeling of vision: The dress by Tom McCoy

 

Bayesian word learning by Tom McCoy (associated homework)

 

Bayesian speech perception: "Planetary" vs. "plant a tree" by Tom McCoy

Neural networks

Perceptrons and gradient descent by Hongru Zhu (associated homework)

 

Computational models of vision by Hongru Zhu

Computational psycholinguistics

Frequency, Ngrams, and Self-Paced Reading by Suhas Arehalli (requires the following files; clicking the links will begin a download: File 1, File 2, File 3, File 4)

 

Probabilistic Parsing and Garden Paths by Suhas Arehalli (requires the following files; clicking the links will begin a download: File 1, File 2, File 3, File 4, File 5)

 

Word Embeddings, Feedforward Networks, and Semantic Similarity by Suhas Arehalli

 

Language Models and Psycholinguistics by Suhas Arehalli

 

PCFGs and Garden Path Sentences by Tom McCoy