Category: Machine Learning

Machine Learning for Everyone by Rob Nowak

Rob Nowak explains Machine Learning, Neural Networks, Deep Learning, Linear Classifiers, Good Features, Principle Component Analysis, Dictionary Learning, Generalization, Cross Validation in this talk called “Machine Learning for Everyone”

Posted in LUCID Library, Machine Learning

How Can Machine Learning Improve Educational Technologies?

by Blake Mason, John Vito Binzak and Fangyun (Olivia) Zhao  As computer-based technologies continue to establish a significant presence in modern education, it becomes increasingly important to understand how to improve the ways that these technologies present educational content and

Posted in LUCID, Machine Learning

Interactive Science Communication

 by Scott Sievert and Purav “Jay” Patel Scientific research is still communicated with static text and images despite innovations in learning theories and technology. We are envisioning a future in which interactive simulations and visualizations are used to enhance how

Posted in LUCID, Machine Learning, Resources, Uncategorized

Singular Value Decomposition (SVD)

By Lowell Thompson and Ashley Hou This is a collaborative tutorial aimed at simplifying a common machine learning method known as singular value decomposition. Learn how these techniques impact computational neuroscience research as well! Singular value decomposition is a method

Posted in LUCID, Machine Learning, Resources

LUCIDtalks: Machine Learning with Ayon Sen

As part of our LUCID program, the graduate students meet weekly and discuss topics that are interesting to both the computation and behavioral graduate students. In this video Ayon provides an overview of Machine Learning in 20 minutes. Ayon explains linear

Posted in LUCID, LUCID Library, Machine Learning

Finding Meaning in Big Data

Discovery Fellows Rebecca Willett and Rob Nowak are creating algorithms to make sense of big data and help machines learn. Full story at wid.wisc.edu.

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How New Yorker Cartoons Could Teach Computers To Be Funny

“The computer models Nowak and his team are developing are called adaptive crowdsourcing algorithms. They attempt to weed out the weakest captions as quickly as possible to get more people to vote on the potential winners.” Full Story on C|net

Posted in LUCID, Machine Learning Tagged with: , ,

The Science of Funny: Active Machine Learning & Cartoons

The New Yorker is using a machine learning system developed by WID Optimization researchers to sort through captions for their weekly cartoon caption contest. See full story on wid.wisc.edu.

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