Original article was published by Bagavan Marakathalingasivam on Artificial Intelligence on Medium
You can Become a Teacher… For Robots?| Machine Learning
Cat or Dog?
Like you or some people you know, there are many people out there that are teaching each other many new things. You are too and may not even recognize. At the same time, even more people are learning something new that they could apply in the real world.
There is a boy named Timmy. Timmy was being taught how to tell the difference between a cat and a dog. Now, Timmy has never seen any of these things before or even knows what they are, but because of your teaching, he was able to detect the difference between a cat and a dog. Here’s the thing, Timmy isn’t actually a real person. You see, this Timmy is actually a machine that was programmed to learn how to tell the difference between cat and a dog. So, how could this machine learn how to tell the difference. Timmy was taught through the use of machine learning.
Machine Learning … What’s That?
So, what exactly is machine learning? Well, as the name states itself its a way to program a machine to learn on its own. With machine learning, the machine will automatically get better and improve with more experience, kind of like humans. As humans, we learn in many different ways. Some people learn on their own, some get taught, some get taught just enough so that they can learn the rest on their own, but how can we make a machine do that. This is where Supervised, Unsupervised, and Semi-Supervised Learning come in to play.
As humans, we learn in many different ways. Some people learn on their own, some get taught, some get taught just enough so that they can learn the rest on their own, but how can we make a machine do that. This is where Supervised, Unsupervised, and Semi-Supervised Learning come in to play.
You’ve just learned about machine learning and now have no idea what this supervised learning even is. First of all, inorder to train a machine we have to give it a bunch of data to learn from. What does this mean? In the example with Timmy, inorder for that machine to learn the difference from a dog and a cat, you would have to keep giving pictures of dogs and cats and telling the machine which one is which. After a while, the machine will be able to know which one is which even without you telling it.
This is how the machine trains, but Well, for starters this is method used to train a machine. What this means is that, when you give data to the machine with the answers. At first we would give Timmy a picture of a dog, and label it as “Dog”. We would do the same thing with cat and label it with “Cat”. Let’s say we show Timmy 50 images of dogs labelled with “Dogs”, and 50 images of cats labelled with “Cats”. After the machine would now be able to tell the difference between a cat and a dog, so if we show a picture of a cat, it would know its a cat.
We know about However, if we wan’t to apply this to the real world, knowing the difference between a cat and a dog isn’t something that could be used. What if we wanted to teach a machine to learn how to play a certain game, or do a certain task. It is going to be hard to give it data to learn from. This is where Unsupervised Learning comes in to play.
This is the opposite of Supervised learning. We would just let the machine run and do whatever it wants. How is it going to learn? We would use something called a rewarding system. This is where if a machine does what you want it to do, or close to what you would want to do, you would give the machine a point. If they do the opposite you would lose a point.The goal for the machine is to get the most amount of points as possible. Since the machine is doing random actions, if it loses a point, it would have a lower chance of doing that action, and vice-versa with gaining a point. Once you keep letting the machine do this, it will slowly start to learn and realise what it needs to do. Pretty cool right?
Let’s say you want to create a machine for facial recognition. You can’t really give a picture of all the people in the