Understanding Machine Learning

What Is Machine Learning?

Machine Learning is essentially about teaching computers to learn from data:

Machine Learning is the field of study that gives computers the ability to learn without being explicitly programmed.

The idea is that there are generic algorithms that can tell you something interesting about a set of data without having to write any custom code specific to the problem. Instead of writing explicit code, you feed data to the generic algorithm and it builds its own logic based on the data.

Let’s say we want to recognize objects in a picture. In the old days programmers would have had to write code for every object they wanted to recognize, e.g., person, cat, vehicles. This is not a scalable approach. Today, thanks to machine learning algorithms, one system can learn to recognize both by just showing it many examples of each. For instance, the algorithm is able to understand that a cat is a cat by looking at examples of pictures labelled as “this is a cat” or “this is not a cat”, and by being corrected every time it makes a wrong guess about the object in the picture. Then, if shown a series of new pictures, it begins to identify cat photos in the new set just like a child learns to call a cat a cat and a dog a dog.

This magic is possible because the system learns based on the properties of the object in question, a.k.a. features.