Arthur Samuel, a pioneer in the field of machine learning, computer gaming and artificial intelligence, defined machine learning (ML) as ‘The field of study that gives computers the ability to learn without being explicitly programmed’.
Machine learning was born from artificial intelligence (AI) and
it has made systems smarter by giving them the ability to make their
own decisions without human interventions. ML gives a learning ability
to machine just like humans. Thus, researchers and computer scientists
are trying to mimic the human learning process and implement it into the
You might be surprised to know that machine learning (ML) is
not just an abstract concept, but is used almost everywhere. Have you
heard of self driving Google car? – It’s the essence of machine
learning!. Online recommendations that you get from Flipkart, Amazon
etc. is machine learning. Many of your
day-to-day activities involve ML such as pattern and image recognition,
network intrusion detection, text based sentiment analysis, real-time
ads on web-pages and mobile devices. Email spam filters?-have you
thought how it’s smart enough to distinguish between spam and important
mails for you! When you start typing the first alphabet in Google, how
it’s able to predict what you want to find? How it gets so clever?? The
secret behind this cleverness is machine learning algorithms.
ML has made it possible to produce models that can analyse
huge chunks of complex data and generate faster results from it. The
result of this ability is that it can make predictions leading to better
decisions and smart actions in real time, without any human
intervention. Not only that, it keeps updating itself with the new data
it receives so as to fit well within the model.
A basic concept like ML has resulted in jaw-dropping
applications like self-driving car, self-controlled drones, robots that
interact with people and communicate with them as a normal human. ML is
creating a new era and our future technology is going to be heavily
driven on ML and deep learning algorithms.
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