Python<\/a>, Matlab, Julia — R. Who would win the battle of the best language for Economic research? That’s probably one of the most common online queries in the programming world. There is just something about humans and our obsession with chasing the very best of the best.\u00a0<\/p>\n Discover Python Projects to Try \u2013 From Beginner to Advanced<\/a><\/p>\n In reality, of course, each language has its nuances and areas And that’s exactly what two London School of Economics researchers did<\/a>. They looked at different languages based on the power of available libraries, the speed and possibilities when handling large datasets, and the speed and ease-of-use for a computationally intensive task.<\/p>\n Hint: the winner has a woman’s name.<\/p>\n That’s the polite University admission exams had been cancelled because of the Well, that one turned out to be even more biased. Close to 40% of students received lower grades than what their teachers had predicted<\/a>, potentially harming their chances to get into their university of choice. Those in working-class and disadvantaged communities were disproportionately affected. <\/p>\n The issue has now been fixed, but it’s a textbook examples of the dangers of AI bias. <\/p>\n
\nin which it shines. Anyone claiming to have a definitive answer on the matter
\nshould come up with some solid arguments to back their verdict.<\/p>\nThanks, but no thanks<\/strong><\/h2>\n
\nversion of what UK students were shouting in front of the Department of
\nEducation over a week ago. The cause of their anger was an algorithm. \u00a0<\/p>\n
\npandemic. Teachers proposed predicting their student’s scores as a way to
\ncompromise. The education department dismissed the idea on the grounds that
\nprevious research had proved such estimates to be biased. Instead, they decided
\nto use an algorithm. \u00a0<\/p>\n