What is Machine Learning? | Oxford Sparks

"Machine learning is all around us; on our phones, powering social networks, helping the police and doctors, scientists and mayors. But how does it work? writes Hyunjik Kim, Machine learning researcher, Seth Flaxman, Computer scientist and Yee Whye Teh, Machine Learning Researcher.

Photo: Oxford Sparks

In this animation we take a look at how statistics and computer science can be used to make machines that learn.


What is machine learning? 
Machine learning is the field of computer science dedicated to teaching computers how to learn from big datasets. An algorithm is a set of rules, a recipe, for a computer to follow. What makes machine learning algorithms special is that they rely on data to work, not a programmer telling it what the rules are; and the more data the better. That means a machine learning algorithm is only as good as its data, so, for example, an image recognition algorithm is going to be very accurate at identifying Big Ben, because there are so many pictures of it on the Internet for it to learn from, but it won’t be as good at identifying your cat Ben, unless of course you happen to post lots of pictures of Ben on the Internet. 

When you combine statistics, which is all about understanding data, with computer science, which is about telling computers how to process data in the most efficient way possible you get machine learning; efficient algorithms that automatically learn from data, improving as they get more data. 
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