The term machine learning and AI(Artificial intelligence) are closely related to each other. The abstraction level of these two fairly draws a thin line and can be interchangeably used.
“Putting down your Terminator movie theory side later”.
The Machine learning and the Artificial Intelligence (AI) are branches of computer science. Machine learning is closely related to data mining rather than AI and you have been quite a using it a lot.
So what’s it exactly?
The data mining (the practice of examining large pre-existing databases in order to generate new information), you see in the email system.
In mailboxes, some of the emails are in Inbox and some of them are in the Spam folder, that is exactly the machine learning rather closely that is data mining. There are huge chunks of data, programs and algorithms are designed in such a manner so that it can predict whether this email is a spam or it’s a good email which needs to be delivered in Inbox.
Its always perfect ‘No’ sometimes it lands up in spam and sometime in Inbox, that is basically a good example of machine learning, at the very small level.
Now things are changing , We are seeing Machine learning version 2.0 in our daily life.
How actually this is working all now days?
There are many components which you have to worried about, first of all huge data set. Data set that can predict a lot of things for example if I show you a chair, everyone can say it’s a chair and if I say that is glass chair, wooden chair, there are thousands of types of chairs (differentiation is important and quite difficult for machine learning).
You can see the difference between all these chairs and still predict the actual characteristics of the chair but w.r.t. to a program, that could have been a nightmare for every programmer. The program can be written like:
A chair has 4 legs and all that, but if I say this can be a centralized table and having a central base and glass sitting area, that is also a type of chair, but it would not be easily written program. For such situations, we require a huge number of datasets that’s problem number 1 (Numero Uno). Secondly, that dataset fetched intosomething known as a classifier which is again big term.
It is understood that more data we are going to have more data prediction but management would be quite difficult. The classifier can classify the image or any other classification is just an example (we just took above). It can predict that image of a chair, some certain amount of confidence can be generated. It cannot be 100% sure but it always about the ratio that the answer would be correct i.e. 90% or less or more.
Conclusion
After this everybody is going to think that in future Machine learning and AI will not need any programmer. Hold down your horses, it is not absolutely true. Few years back when computer were coming everyone was talking , if computers opposing they will take their job. Did computer even try of that? Perhaps the computer purposed a number of jobs as compared to others. So the same thing applied over here, no one knows about the future. There may be chances that a number of jobs may open. The scenarios may change and the future cannot be predicted completely.
Always remember All early mornings and late nights will pay and work hard.
Click here to know more : https://www.ethans.co.in/en/python-training-in-pune
Click here to know more : https://www.ethans.co.in/en/python-training-in-pune
