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Adapting Machine Learning Algorithms to Novel Use Cases
Editor’s Note: Kirk will present his talk “Adapting Machine Learning Algorithms to Novel Use Cases” at ODSC West 2019. If there was a metric for success in the data science profession, it would require a multi-dimensional scoring model. This metric would cover a data scientist’s technical skills and talents,... Read more
Search engine battle: Is Yandex’s neural net algorithm better than Google?
Yandex, one of Russia’s biggest Internet companies and a popular search engine, introduced a new deep neural search algorithm this week named “Korolev.” RBTH tested it against Google to find out which search engine is better at understanding user requests. Yandex said it’s new algorithm, “Korolev,” is better at... Read more
How We Game the Algorithm to Tame the Algorithm
Algorithms are everywhere. Sometimes we see traces. Once in a while we feel the effects. Mostly, we go about our days vaguely aware of an invisible algorithmic presence. We set out to learn how people live with algorithms now and what it means for the future. One thing became... Read more
Ethics for powerful algorithms (1 of 4)
COMPAS has been in the news a lot lately. It’s a proprietary algorithm widely used by judges and parole officers to set bail, adjust sentences, and determine terms for parole. If you are arrested in the U.S. today, COMPAS or an algorithm like it will likely influence if, when... Read more
The Five Faces of Algorithms
Or, How We Conceptualize The Invisible Algorithms are everywhere. Sometimes we see traces. Once in a while, we feel the effects. Mostly, we go about our days vaguely aware of an invisible algorithmic presence. The goal: to make invisible algorithms more visible. So, I designed challenges to provide a... Read more
A Stochastic Gradient Descent Implementation in Clojure
Description of the problem Gradient Descent is an algorithm that finds local extremum points of a real valued function with several variables.  As such it is a go-to algorithm for many optimization problems that appear in the context of machine learning.  I wrote an implementation optimizing Linear Regression and Logistic Regression cost functions in Common Lisp... Read more