Machine Learning: What It Really Is & Why It’s Important

With technology playing a more prominent role in our lives each day, you’ve probably heard the term ‘machine learning’ thrown around — but do you know what it means or why it is important? While some of you are answering yes to these questions, there are just as many who aren’t quite sure about machine learning. We’re going to shed a little light on this for you.

What exactly is machine learning?

Machine learning is an excellent method of analysing data whereby analytical model building happens. To make it easier to understand, here are some explanations from some experts:

In classic terms, machine learning is a type of artificial intelligence that enables self-learning from data and then applies that learning without the need for human intervention. In actuality, there are many different types of machine learning, as well as many strategies of how to best employ them,” explains Fran Fernandez, head of product at Espressive

“Machine learning is the science (and art) of programming computers so they can learn from data,” writes Aurélien Géron in Hands-on Machine Learning with Scikit-Learn and TensorFlow.

“Machine Learning is the science of getting computers to learn and act like humans do, and improve their overall learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.” — Emerj (AI Research and Advisory Company)

Why is machine learning important?

The amount of data available is infinite, and with the affordability of data storage and the availability of powerful processing, machine learning has grown. While machine learning is used by many industries and organisations and adapted to suit their specific wants and needs, overall, it is fantastic for enabling organisations to identify potential risks and more profitable opportunities quickly.

Examples of Machine Learning in society today

Take a look at a few widely publicised examples of machine learning applications you may be familiar with in the world around us today:

  • The self-driving Google car is an excellent example machine learning at work.
  • Online recommendation offers such as those from Superbalist and Netflix? These are Machine Learning applications for everyday life.
  • Fraud detection? This is one of the more obvious and vital uses of Machine Learning in our world today.

Machine Learning at Riskworx

Our team of innovators at Riskworx has been applying a Machine Learning approach to reducing Peer-to-Peer Credit Risk Management costs, something which will be of great use to the financial services industry. They have put together a paper that explores the use of Machine Learning models to enhance credit management in the context of Peer-to-peer lending with the view of unlocking its full potential.

Now that you have a better understanding of Machine Learning, be sure to check out this paper here.