Introduction to Machine Learning

Imagine you are with a toddler and you are teaching her how to hold a pen. She will hold it and then drop it. You will again take the pen and teach her how to hold. This process multiple tomes till she gets it.

That is the same way Machine learning works.

Machine learning is the process of teaching a computer system how to make accurate predictions when fed with data.

ML is a subset of the larger field of artificial intelligence (AI) that “focuses on the development of computer programs that can access data and use it to learn for them. The primary aim is to allow the computers to learn automatically without human intervention or assistance and adjust actions accordingly.”

For e.g. we all binge watch Netflix, and as soon as we open Netflix, it will start providing us with recommendations on what to watch next. This is because, Netflix taps the streaming history and habits of its millions of users, to predict what individual viewers will likely enjoy.

Another example is Intelligent personal assistant (IPA) specially designed for particular tasks, such as Apple’s Siri in iPhone, Microsoft’s Cortana, Google Voice Assistant. With the help of these intelligent personal assistants you can find out anything you want.

In all of these instances, each platform is collecting as much data about you as possible, what genres you like watching, what links you are clicking, which statuses you are reacting to, and using machine learning to make a highly educated guess about what you might want next. Or, in the case of a voice assistant, about which words match best with the funny sounds coming out of your mouth.

Frankly, this process is quite basic: find the pattern, apply the pattern.

But, this aspect of Machine learning today, pretty much runs the world. From going on websites like Amazon, to Netflix, to Alexa, our world is runs through machine learning. So next time, observe how much AI and Machine learning is impacting you.