One of these days, as a programmer you must have walked past a group of people discussing some data sets and talking about Machine Learning. Intrigued, you must have gone home and googled it. So, today we bring you the A-Z of Machine Learning – what it is and why you should consider Machine Learning as a career prospect.

What is Machine Learning?

As the name suggests, Machine Learning is making the computer “learn” using various examples and data inputs. This definition is rather crude but does explain the overall meaning of Machine Learning.

Now, taking the crude definition in mind, let’s see what Machine Learning is with an example –

Let’s take up an example of a machine or a system which has the capability to sort out fake signatures from the real ones. Now, to make such a system, the machine needs two things – a real signature for a reference and a data input which will be matched. Now, if we hire someone for this job, he/she will check the curves from the real one and see if the input one has 80-90% similarity before turning it in as real signature. But for a machine it’s not that simple, the machine needs an algorithm using which it can match the two signatures. The algorithm needs to be generic as well, because we can’t be writing algorithms for every person’s signature. The machine should be able to identify the various curves and design of the real signature and generate a logic on which it tests the input signature.

Such type of algorithms which without changing any code, generates a logic of its own to perform a specific operation are Machine Learning algorithms.

Types of Machine Learning

There are 2 types of Machine Learning –

Supervised and Unsupervised Machine Learning.

The difference between them is really simple and easy to understand.

If you have some data based on your experiences or taken from some source and then you feed it to the machine to perform some tasks. This is known as Supervised Machine Learning.

While, if you don’t have some concrete data, you have some basic information and you then feed it into the machine, it is called Unsupervised Machine Learning. The machine in unsupervised machine learning can make algorithm to identify patterns to reach a result.

Let’s take an example that you are a real estate agent and you want to buy a house in some area. You decide to create an app which would predict the price of the property by using some basic information such as area, amenities etc. In a supervised learning, you would feed the machine examples such as your previously bought properties and its prices and that would be a reference for the machine.

In an unsupervised learning, you just give the machine basic information such as area of the property, amenities and leave it up to the machine to figure out the prices. Without any prices, an approach to such kind of problem can be figuring out different property segments and their general prices.

Machine Learning as a Career Prospect

Machine Learning is one of the basic steps in Artificial Intelligence and Deep Learning. In our world, where data is everything the concept of Machine Learning is a must. Handling such large amounts of data and processing it with ease is must. Using Machine Learning and applying the concept of Neural Networks, the research in this field is headed where a machine can replicate the human instinct of learning and not just estimating using some input data.

Today’s Machine Learning Algorithms are crude and we are only able to solve a specific problem with a limited scope. As a career option, Machine Learning has a much greater potential and scope. Machine Learning essentially serves as a basic building block to AI and therefore it offers a rich and a powerful scope as a career option.