Wait a minute! Learning from past experiences is something humans do, right? Exactly! The computer folks want computers to behave more and more like us. As if there aren't enough of us already. As the machines are becoming more like us, we are becoming more like them.
Introspection time! Most of us wake up every morning like clockwork! Then we rush through the morning routines - get dressed, wade through the traffic, and reach our offices or schools or wherever people expect us to be. We spend the most hours of most days of our lives there, doing what we call our work or our duty. What exactly is this work? In most cases, it would be a set of instructions laid out to us by some higher authorities.
Let us assume that you work at a tea stall. You could be spending most of your time boiling milk and adding tea leaves and sugar to it. When the milk boils, it rises up almost instantaneously and spills over the pot. Obviously, you did not know that when you started the new job. It is when the milk actually got spilt and your superior made you clean up the mess, you realized that the stove must be turned off or the flame be lowered as soon as the milk is boiled. Here, you learned something from an experience. In very basic terms, this is the very essence of machine learning.
How do we make machines learn? Well, the techies have come up with some cool techniques to go about that. While there are numerous techniques, the most common ones include classification, regression, clustering, and reinforcement learning.
This is not a series on Machine Learning. Therefore, we would not be discussing the techniques in detail. However, in the following write-ups, we shall take up some of the machine learning terminologies and look at how we have been applying similar concepts in our daily lives in a not so right manner, and how to unlearn the same.
Unlearn? Let’s find out.