Importance of Machine Learning

Lately, everywhere we go, internships, job offers, courses, training and pretty much everything seems to be about machine learning. Casually scrolling through the Instagram feed, we often find articles and pieces of news about it. It is everywhere around us. So, why are industries and companies so fixated on this technology in recent years?

Origin of Machine Learning

It is evidently hard to deny the growing influence of machines in every field. The importance of automation defines the future of humanity. The concept of machine learning has been around for a long time. To be precise, it dates backs to over sixty years during World War II when Alan Turing formulated the ‘Turing test’ to ascertain whether a computer had intelligence. 

But, machine learning has come to the spotlight just recently because of the many leaps and bounds in modern technology. Some of its applications that most of us are familiar with are Google self-driving car and personalised ads and recommendations from Amazon, Spotify and Netflix. 

What is Machine Learning?

For the ones who are new to this, to put it in simple words, machine learning is training a computer to learn, to identify patterns, and to perform tasks by itself by feeding it with a large amount of data. The more information we provide, the more accurate are the outcomes we receive.

We use many algorithms to teach the computer to recognise the features and characteristics of an object. For example, if we showed it a picture of a banana and told that it was a banana, it stores the information and builds upon it every time a piece of new information is fed. If we show an image of an orange next, it learns to differentiate it from the banana.

Advantages of Machine Learning

From scaling down the time consumed in completing various operations to cutting down errors from human intervention, machine learning provides an abundance of advantages. It tremendously helps companies to enhance their overall productivity, functioning and decision-making processes. With the expanding volume and varieties of data, computational processing could provide a much cheaper, affordable and robust data storage. The efficiency and accuracy of machines are unparalleled. 

Applications of Machine Learning

Machine learning plays an indispensable role in almost every industry. Financial services such as banks and the government use it to identify necessary data insights, prevent fraud and curtail identity theft. Website retailers rely on it to analyse previous purchases of buyers and produce a customised shopping experience. It is an essential tool for delivery companies, public transportation and other organisations to predict traffic-free routes. With the advent of wearable devices sensors, the healthcare industry has a much easier time tracking the health of patients in real-time. 

Some popular machine learning methods

From numerous categories of machine learning, the two most widely used methods are supervised and unsupervised learning. 

In brief, supervised learning is teaching machines using well-labelled data to produce the correct outcome, whereas the latter is training the computer with unlabelled data to find the hidden patterns in data.

Initially, you may feel intimidated by machine learning due to the multiple misconceptions and limited knowledge you possess on the subject. But, it is very different, challenging and exciting once you delve into it.