Machine learning: what is it and what is it for?

Machine learning is nowadays a hot topic and with great development, especially for the advantages, it brings to organisations and how it helps to solve some business problems.


Machine learning technologies are an area of ​​artificial intelligence that allows you to create systems that can learn to make decisions with reduced human interference. These systems, instead of simply following their user's “orders”, adapted from previous calculations and decisions, returning results without human interaction on a continuous basis. It allows software applications to be quite accurate in predicting results, even without being expressly programmed to do so.


Machine learning systems are based on algorithms that analyse data, “learn from them” and are in a constant process of improvement, considering the different situations they face. Instead of being a system programmed by rules, machine learning systems work with algorithms that create the system's own rules, which can be supervised by human hands only if necessary.

Data is one of the most precious assets for the business, boosting the development of technologies related to artificial intelligence, such as machine learning algorithms. The use of these algorithms has become more interesting with the increase in the number of data generated by us and our devices. More data means more material for the algorithms to be able to make better predictions.


Organisations are using these algorithms to recognise patterns and then build predictive models about future consumer preferences, find ways to improve their internal processes or improve their products. By incorporating machine learning algorithms in their operations, they have a greater competitive advantage and allow them to solve business problems, and have efficiency gains in the organisation by reducing operating costs. At the same time, unravelling consumption/behaviour patterns, revealing market trends, identify customer preferences, and more easily attract the “right customers”. The results for the organisations that use them are very promising and the problems that the algorithms help to solve are very varied, such as data insertion, data quality, predictive maintenance, spam detection, improving cybersecurity mechanisms, boost sales, simplify marketing actions, among others.


And from financial services, state, health, transport, to retail, there are many business areas that currently use machine learning to perform advanced calculations, improve the productivity of their teams or simply provide better customer service.

In fact, this is a method of data analysis that is so established in our day-to-day life that we hardly realize its use, given all our familiarity with it. For example, Amazon recommendations, web searches and automatic translations for the Google service are based on machine learning algorithms.


Although machine learning algorithms are one of the most revolutionary technologies in recent years, the adoption of these technologies by organisations is still very recent. In the future, the benefits of these algorithms will be even more diversified, providing organisations with improvements in productivity, the possibility of predicting market trends and, of course, providing an excellent service to the customer.


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