Cathy O’Neil’s Weapons of Math Destruction, when it was first published in 2016, sounded an early alarm about the big data algorithms and their potential for social evil. The cover is adorned with a robotic death’s head and the subtitle reads “How Big Data Increases Inequality and Threatens Democracy.” O’Neil’s book begins with stories thatContinue reading “Book Review: Weapons of Math Destruction”
Daily Archives: April 8, 2019
Historical Spotlight: Alan Turing
80 years ago, in 1939, Alan Turing began work on the code-breaking system that would eventually prove key in helping Britain survive the German submarine threat in the Atlantic. Last month, the Turing Award in computer science prize (sometimes referred to as the “Nobel Prize of Computing”) was given to three researchers, Yann LeCunn, GeoffreyContinue reading “Historical Spotlight: Alan Turing”
Confusing Terms in Data Science – A Look at Synonyms
To a statistician, a sample is a collection of observations (cases). To a machine learner, it’s a single observation. Modern data science has its origin in several different fields, which leads to potentially confusing synonyms, like these:
Confusing Terms in Data Science – A Look at Homonyms and more Synonyms
To a statistician, a sample is a collection of observations (cases). To a machine learner, it’s a single observation. Modern data science has its origin in several different fields, which leads to potentially confusing homonyms like these:
Confusing Terms in Data Science – A Look at Synonyms, Homonyms and more
To a statistician, a sample is a collection of observations (cases). To a machine learner, it’s a single observation. Modern data science has its origin in several different fields, which leads to potentially confusing homonyms and synonyms, like these: Homonyms (words with multiple meanings): Bias: To a lay person, bias refers to an opinion about somethingContinue reading “Confusing Terms in Data Science – A Look at Synonyms, Homonyms and more”