What is Machine Learning, and How Can Your Business Use It

What is Machine Learning, and How Can Your Business Use It

Machine learning is one of those concepts that everyone has heard about but few really understand. Let me step you through what it is and how businesses use it.

Machine learning, sometimes known by the acronym ML, is a subset of artificial intelligence. It refers to software that has self-learning or self-improving capabilities which can predict and react to unfolding scenarios based on previous outcomes.

You might not notice it, but machine learning is already part of your daily life. For example, Netflix uses machine learning to offer you personalised recommendations for series and movies. It’s a technology that’s moving into prime time as businesses accumulate more and more data and look to take advantage of it.

Here are the three key types of machine learning that matter: 

Supervised Learning

This is the most popular paradigm for machine learning, the easiest to understand and the simplest to implement. It is when an algorithm learns from data and associated target responses that can consist of numeric values or string labels, such as classes or tags, to later predict the correct response when posed with new examples. For example, using a set of conditions (age, expenditure, marketing channel responses, etc.) to predict a business outcome (buyer/non-buyer).

Unsupervised learning

Unsupervised learning occurs when an algorithm learns from. the data to identify associated purchase patterns. Unlike supervised learning, this type of machine learning model does not follow a set of business conditions to predict an outcome. Instead, it can be used to, for example, predict the product genres a customer is likely to buy and create customised recommendations for them in their checkout basket. Another example: Travel agencies can use unsupervised learning to identify a tourist’s travel patterns and, using that information, to promote specific travel packages to them.

Reinforcement learning

This category of machine learning is very behaviour-driven. It takes actions in an environment where the aim is to encourage the use of cumulative rewards. This model can be found in automated vehicles where, instead of many “if-then” commands, programmers prepare the “reinforce learning” algorithm to learn from a system of rewards and penalties to minimise accidents. Another example of reinforcement learning is music streaming platforms. Instead of using multiple “if-then” commands, these platforms use reinforcement learning to understand and learn from a user’s likes, dislikes, and music preference behaviours to recommend them a weekly music selection.

Those are the main types of machine learning in use today although. Here is, of course, a lot more to know about how data is harnessed in the service of business strategies.

If you think the potential of artificial intelligence and machine learning is out of the reach of your business, think again. Data Science Solutions from DSS unlock the power of Big Data for organisations. Our team looks forward to understanding your business objectives and rafting a data science solution to help you reach them.

Jarrod Teo, chief data scientist, DSS.

No Comments

Post A Comment