What is Machine Learning and how to get started with Machine Learning?

“COMPUTERS ARE ABLE TO SEE, HEAR AND LEARN. WELCOME TO THE FUTURE” –  DAVE WATERS

 

In this article we will go through what is machine learning and what are the steps to learn machine learning So let's get started! Now the terms - Machine learning and AI artificial intelligence is closely related And it's not wrong to say that the abstraction level of between these two words is fairly thin line and they can be  used Interchangeably. Let's talk about machine learning and AI. Now machine learning and AI  are branches of computer science. They are closely related, but according to me, what my personal thought is machine learning is closely related to data mining rather than AI. AI is completely a different thing But what you think of machine learning is closely related to data mining And you have been already using it quite a lot. Now, you might be thinking where We are already using machine learning? Now although you have just heard the term machine learning But you might already be aware of the term known as data mining.

 

 Now Data mining has been there since the evolution of data and computers which have been into the world quite a lot and all the things that you see. Simple examples would be Spam emails. You see that some of your emails are in your inbox and some of them are into Spam box. What is that? That is machine learning! Rather closely that is Data mining. There is a huge chunk of data and your program and algorithm is designed in such a manner So that it can predict that whether this email is spam Or is it a good email that needs to be delivered in Inbox. But it is not always perfect, sometimes good email also land up in the spam and spam email lands up in the inbox. So that is basically a good example of machine learning, at a very small level. But now things are changing. That was Version 1.0 of machine learning. Now what we are seeing in our day to day life is machine learning Version 2.0. So, how actually this is working all nowadays? So if I talk about the machine learning at a very broad scale There are a couple of components that you need to be worried about. First of all, is a huge data set. Data set that can predict a lot of things, for example If I just show you a chair you can say that's a chair! But if I say that that's a wooden chair, that's a glass chair And there are tons of types of chairs. You can see the difference between all these chairs and can still predict that that's the chair. But if I just ask you to write a program for that, that could have been nightmare for you.

  For example If you are just writing a program that it should have a four legs and some wooden texture That would be a chair. But what about when I say that it can be just a centralized table, having a central base and a glass sitting area That is also a chair, but you cannot write a program for that and for such situation We require a huge number of Data sets. That's problem number one. The second thing that data set is being Pitched to something known as classifier Which is again a big term, but rather I would say that is just an algorithm which can Determine the output based on whatever the Data is being fetched. And as we all know the more data we are going to have the more prediction capability is going to be there. So now based on what kind of data You are supplying, your classifier can classify the image or any other thing. In this example We are just taking an image of chair so it can predict that image of chair with some certain amount of confidence that it can be chair. It can never be 100% sure but it's always about the ratio of How much confidence that it's showing that ab is that 99% chair? Is it 80% chair and is it 70 percent chair?

 

 

“A question that I feel everyone have in their minds is that in future  AI and the machine learning are going to learn to write the code So there will be no need of programmer.”

 

But I don’t think so because with the evolution things changes quite a lot I do agree But this is almost similar to the strike that I saw in my childhood, when people were opposing the computers. Everybody in the government department Private sector was saying that hey if computers will come up They will take our job. Did computers did that? Perhaps!

 

But  it did  open more number of job as compared to that the job that is taken. The same thing Is applied here. AI and Machine learning  are  going to take the job of programmers? Who knows ? But is it going to open up more more Responsibilities and more scenarios of working jobs? For sure it is going to be there! So on a whole note There is no such thing to be worried about that  in future machine learning and AI wont take our jobs  instead in future there is more demand of programmers to understand that data . In fact we do need more programmers in future. So now that you understand that how machine learning work on a simple scenario, a huge number of Data set being given to classifier and based on that data set, it just do some processing and tries to predict the results. That is  basically machine learning and machine learning is being applied being applied at a lot of places. Spamming is one of them. Recently, Tesla created automated cars that can be driven without a driver ,what do you think? Its all based on machine learning.   That's just one example of machine learning. Have you used some kind of app which predicts- How you will look like in your 80's or your 90’s. How your face is going to get at some deformation? Your skin is going to get some kind of deformation. This is all based on machine learning. So now that on a very big scale you understand, what is machine learning,

 

 

 

 

 

How you can get started in machine learning?

Now there are a couple of ways of getting started in machine learning and everybody has its own implementation of machine learning.

So how you can get started with machine learning? Machine learning is first of all dependent quite a lot in math, but not all the time It's going to be like designing your neural networks or designing your patterns and all these things. It's not all the time about that but based Example or base core setup of machine learning is dependent on that as well, but the first language that you should be looking up in order to get started with machine learning is Python. Python being the very first language for took advantage and brought us up the libraries like  Tensor flows and lot more . Obviously the language has its perks, And it is being heavily used in machine learning. Now before you get started and jump directly into the  tensorflow Documentation and everything, let me tell you that Python needs to be there in your pocket. Nobody is going to teach you in a machine learning course that  how to write a loop or how to loop through an array or how to define these set of lines into a function or create a new classes. These are all basics that you should have Already in Python.

 

 

 

 

So Python is the one way of getting started with machine learning and most people think that's the only way But that's not true. There are other languages also that are coming up with machine learning like R, Scala etc. R is used in data analysis and statistical computations. The best language for machine learning depends on the area on which it is going to be applied. For Example Javascript is the most widely used language to improve web development. Developers who are new to  to data science and machine learning prefer Javascript for enterprise focused applications.