Share on LinkedInTweet about this on TwitterShare on Google+Share on FacebookShare on Reddit

Ten Myths About Machine Learning

Go to the profile of Pedro Domingos
Professor of computer science at U. Washington and author of “The Master Algorithm”. pedrodomingos.org
10-myths-about-ml

Machine learning used to take place behind the scenes: Amazon mined your clicks and purchases for recommendations, Google mined your searches for ad placement, and Facebook mined your social network to choose which posts to show you. But now machine learning is on the front pages of newspapers, and the subject of heated debate. Learning algorithms drive cars, translate speech, and win at Jeopardy! What can and can’t they do? Are they the beginning of the end of privacy, work, even the human race? This growing awareness is welcome, because machine learning is a major force shaping our future, and we need to come to grips with it. Unfortunately, several misconceptions have grown up around it, and dispelling them is the first step. Let’s take a quick tour of the main ones:

Machine learning is just summarizing data. In reality, the main purpose of machine learning is to predict the future. Knowing the movies you watched in the past is only a means to figuring out which ones you’d like to watch next. Your credit record is a guide to whether you’ll pay your bills on time. Like robot scientists, learning algorithms formulate hypotheses, refine them, and only believe them when their predictions come true. Learning algorithms are not yet as smart as scientists, but they’re millions of times faster.

READ FULL ARTICLE

Share on LinkedInTweet about this on TwitterShare on Google+Share on FacebookShare on Reddit

Blog Publisher / Head of Data Science Search

Founder & Head of Data Science Search at Starbridge Partners, LLC.