When it’s time to learn “Machine Learning”, the first thing that you will hear is “Types of Machine Learning”. Because this is where you will begin to learn.
Based on learning algorithms, machines can learn in two ways. In supervised way and the other is un-supervised way. So these are the types of machine learning. Let’s discuss about them with examples.
1. Supervised machine learning
Here at the very beginning you teach your machine. Then the machine gives you result based on your lessons. Let me give you a real world example:
Suppose, you want to teach the machine to recognize images of fruits. In supervised learning process you show the image of apple and tell machine that this is apple. Again you take image of orange and let it know that the image contains orange.
By this way you teach your machine with lot of images and their labels.
After that, if you show a new image to the machine, most likely it will recognize the fruit’s name.
2. Unsupervised machine learning
Here you don’t teach machine. It learns itself. Lets jump into an example. In this scenario, you show many images of apples and oranges. But don’t say which one is apple and which one is orange. The machine will be able to predict that these two things are different. It will categorize apple in one category and orange in another category.
That is, it will cluster different things in different groups.
Isn’t it that simple?