Machine Learning is a very eminent buzzword these days. Everyone’s talking about it. But what does it mean exactly? If you’re a newbie in this domain, look no further!

According to seedscientific.com we generate 3.7 quintillion bytes of data every day !😵 With so much data at hand, imagine what all information we could garner that could help make our lives simpler and more meaningful. This is what machine learning is capable of. In Machine Learning, machines are essentially made to learn from data that is available by training them just like a child is trained to learn new things.

Imagine these “trained” machines as a black box, wherein you feed it raw data and it vomits out pure gold information! 😍

To make you understand let’s take a real life example. If I show a robot 1000 pictures of cat and 1000 pictures of dog and tell it which animal each picture contains every time I show it one, then eventually it’ll start to identify certain features that are characteristic to cat and certain that are to a dog. Now if I show my robot a new picture of a cat, it will be able to a say that it is a cat and not a dog. Why, you ask ?? Well….because it has been LEARNING the features of each of the animals before. That’s what’s called training our robot/machine.

Machine Learning is used basically for two things :

Predicting stuff Making sense of data by finding patterns in it In tech lingo, ML has been divided in two parts: Supervised ML and Unsupervised ML. In Supervised ML, you have a dataset containing a set of features X and target labels Y. The model’s job is to learn the mapping function Y=f(X).

There are two main types of problems in Supervised Learning viz. Regression and Classification. Regression involves predicting a number whereas Classification involves predicting a category of data.

In Unsupervised ML, you don’t have X and Y. The model is given just the data, with no target label and its job is to extract patterns from it. Clustering and Segmentation are pretty popular use cases of Unsupervised ML.

Machine learning is all around us. From personal assistants to recommendation systems in YouTube, Netflix and even on Medium 😅, from spam classifiers to driverless cars, machine learning is taking over the planet! So if you don’t wanna lack behind, hop up the AI train and explore this new electricity of 21st century .

Well this sums up our mini introduction to machine learning. You can only go up from here now that you know the basics of ML.

All the best !