What is machine learning?

By Kayleigh Shooter
Machine learning technology is growing everyday and is being deployed throughout all industries, but what exactly is it...

 Machine learning (also known as ML) is the study of computer algorithms that improve automatically through more and more experience. Machine learning tends to be seen as a subset of artificial intelligence (AI) as they work hand in hand together. Machine learning algorithms build an intelligent mathematical model based on sample data, also commonly known as "training data", which allows it to create predictions or decisions without being specifically programmed to do so. 

Machine learning, whether you know or not, is integrated into your day to day life. For example, when you are scrolling through Instagram, machine learning is working hard to personalise your feed to your interests and personal needs. Similarly, once you view an item on your browser, similar items will be advertised to you through multiple channels, this refines your shopping experience and recommends products that may be of interest to you. 

A more in-depth example of a use of machine learning when Netflix Netflix held its first "Netflix Prize" back in 2006, the competition was to find a program to better predict user preferences and improve the accuracy on its already existing movie recommendation algorithm and service by at least 10%. This was used to enhance the user experience and ultimately get users to stay on the site/application for longer if their movie recommendations were correct and specific enough.

Machine learning is able to easily identify trends and patterns by reviewing large volumes of data and discovering specific trends and patterns that would not be apparent to humans. The technology is continuously improving and advancing which allows for continuous improvement and therefore improved accuracy and efficiency.

However, machine learning requires lots of effort and time, this is because you will need to allow the algorithms to learn and develop enough to fulfil its purpose with a high level of accuracy, this will take a lot of time and effort to set up and develop. It will also require a large number of resources, which could be costly and also time-consuming. 

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