Have you heard the term “machine learning” and wondered exactly what that entails? Machine learning essentially gives computers the ability to “learn.” Arthur Samuel coined the term in 1959 and it has been growing and changing ever since. Let’s explore what exactly machine learning encompasses.
Our ability to learn and get better at tasks through experience is part of being human. When we were born we knew almost nothing and could do almost nothing for ourselves. But soon we are learning and becoming more capable by the day. Did you know that machines can do the same?
Machine learning brings together computer science and statistics to enable computers to do a given task without being told to do so. Say you need a computer that can tell the difference between a dog and a cat. You can begin by giving it pictures of both animals, and telling it which is which. A computer programed to learn will seek statistical patterning within the data that will enable it to recognize a cat or a dog in the future.
It may figure out that dogs tend to be larger, or that cats have small noses. It will then represent that numerically, organizing it in space. Crucially, it is the computer and not the programmer identifying and deciding those patterns and establishing the algorithm by which future data will be sorted. The more data the computer receives, the more finely tuned the algorithm becomes and the more accurate it becomes.
Machine learning is already widely applied. It’s the technology behind facial recognition, credit card fraud detection, text and speech recognition, spam filters on your inbox, online shopping recommendations, and so much more. At the University of Oxford, machine learning researchers are combining statistics and computer science to build algorithms that can solve complex problems more efficiently while using less computing power. From medical diagnosis to social media, the potential of machine learning to transform our world is truly mind blowing.