The Basics of Machine Learning

If you read all those books and looked a little bit around the internet you would probably be able to know what is machine learning but for me, I like the Arthur Samuel definition: " A field of study that gives computers the ability to learn without being explicitly programmed", In summary, machine learning is a sub-field of artificial intelligence, where we design systems that can learn from a provided data by training it. There are 4 types of machine learning but two of them are the most used, Supervised, and unsupervised learning. It is basically when you know the output so working with a set of labeled data, let's say a classic example is to classify email messages into spam and non-spam you basically feed the algorithm with the input and the output and based on it the algorithm would eventually predict a class out of a never seen data based on experience. Supervised machine learning includes two major processes: classification and regression. On the other hand, you have unsupervised learning, in which you let the algorithm learn on its own, formally let the algorithm find a hidden pattern in a load of data, there is no right or wrong answer, you are just training it and looking for the patterns it generates.