Machine Learning: How can you apply it to your business?
22 de October de 2020
22 de October de 2020
Technology never rests. It constantly advances at such a speed that it is practically impossible to keep up with the pace. Artificial intelligence, big data, the Internet of Things, etc., all these trends signify big changes both in terms of the world we live in and the business sphere.
However, with respect to the business/technology crossover, there is one trend in particular that is the subject of lots of talk right now: Machine Learning. Why is there such a buzz? What is Machine Learning and how is it transforming the business world? The lecturer at EAE Business School and CEO of Recúbica answered these and more questions in a talk entitled “Machine Learning: Applying it to your business”.
Would you like to know his insights? Let’s find out.
What is Machine Learning?
First of all, Ángel Barbero focused on the definition of the term because, although it is constantly heard these days, few people stop to ask themselves what Machine Learning really means?
According to the expert, Machine Learning refers to “the tools that enable us to gather data and which, through algorithms, let us group and classify this data and detect its behaviour”. Therefore, it is considered to be a great field of knowledge that analyses how and what machines learn from data.
Barbero explained that, while Machine Learning is one of the most important areas of Artificial Intelligence, the two concepts are not exactly the same thing, so they should not be confused.
Types of Machine Learning
So, are all machines designed to learn in the same way? Does Netflix’s Machine Learning work in the same way as Nasa’s? The answer is no. There are the following 3 main types of Machine Learning:
Barbero explained that Machine Learning identifies responses to questions that we have not asked. In other words, it helps us discover spaces that we did not know beforehand. The machine is given a dataset, but it is not told anything about this data set. It probably is not even labelled. The machine then takes the data and tries to perform classifications based on the patterns it finds in the data set.
To give a more in-depth explanation, the lecturer gave the following example: “If you have a computer that learns in this way and you give it a group of images, it automatically classifies them by colours, the presence of people or animals, or many other variables. Therefore, when it processes the data, it can give us unexpected results that we did not even ask for. In this case, it is the machine itself that decides. As such, the more information the data contains, the better and more comprehensive the classification it shows us will be.
Supervised Machine Learning is the most common case, as it involves a significant human component. “There is human supervision, which facilitates data processing”, explained Barbero. “We give it some groups of data with possible combinations and results. With this model, the machine learns and infers behaviour and acts on it”.
Supervised Machine Learning enables us to identify images, detect fraud, retain customers and loads more. Just as in the case of the unsupervised version, in Supervised Machine Learning, the quantity and quality of data input into the machine is absolutely crucial.
Last but not least is Reinforcement Machine Learning, which involves machines that learn based on trial and error in response to data or data requests.
“It is a smart agent with a superior algorithm that enables it to execute and process data, as well as acting on and learning from what it does with this data”, explained Barbero.
Machine Learning in the business world
As Barbero explained, we cannot discuss Machine Learning without talking about data, because it is precisely this data that enables Machine Learning to become an almost indispensable tools for the exponential and effective progress of businesses.
Why is data so important? Because they represent information that, if correctly processed through Machine Learning, enables us to gain greater insight into our customers, streamline processes, optimize our products and, ultimately, improve every aspect of our business.
“Now is the time to bring the user closer to the result that they are looking for, without them even knowing”, explained the lecturer, as Machine Learning not only helps you to get to know your customers better, but also to anticipate their tastes and needs. Therefore, it has the power to offer them a result that they were not even looking for but which they already had in mind. This certainly opens up an endless range of opportunities in terms of satisfying customers.
Machine Learning is now used in an extensive range of sectors, such as talent management, communications, logistics, commerce and many more. However, Barbero emphasized that the “crucial thing is to understand the origin of the data and, most importantly, analyse how we build the result that we want to show to the customers”.