Smart apps with learning capabilities are not new. The first programs with these capabilities date back to 1952. However, due to the increase in digital information, the term Machine Learning, one of the branches of Artificial Intelligence, is taking hold later in the business world.
New Machine Learning algorithms help solve corporate problems using more efficient and more accurate ways than with outdated prediction techniques.
Although most consumers don’t know it, different Machine Learning methods are being implemented at high speed in a large number of everyday situations. Here are 4 of the best-known ways to use Machine Learning these days.
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Machine learning systems are becoming more advanced, so they are able to understand the language with which we relate to humans and can respond to us in our own language. This is called Natural Language Processing.
The Natural Language Processing saves time and streamlines work by automating processes done by hand, allowing us to make decisions more easily.
Tools Data Mining (Data Mining) explore within large databases, automatically or semi-automatically, with the aim of finding repeating patterns, trends or rules that help us to explain the behaviour of the same data in a given context.
What can data mining be used for? The most outstanding applications in the business world are the following:
Thanks to modern systems that use data mining, we streamline the tasks of our companies to be more efficient.
The Vision ( Computer Vision ), scientific discipline, is concerned with developing artificial systems that obtain information from multidimensional data. That is to say, the Artificial Vision includes processes to acquire, process, analyze and understand images of the real world in which we live in order to produce numerical or symbolic information that can be processed by a computer.
Some of the best-known applications of Machine Vision in the business world:
Artificial vision helps to achieve strategic objectives in terms of product quality improvement, increased productivity and reduced production costs. The data collected on parts defects provides an opportunity to identify and fix production line problems.
The term “Robotic” is usually incorporated into that of Artificial Intelligence, but not all robots are “Intelligent”. Robots are machines that do a job for themselves, following a set of rules programmed by a computer. Currently, AI and Machine Learning are applied in a limited way to enhance the capabilities of industrial robotic systems.
Supply chains and companies specializing in logistics applications are among the first to implement Artificial Intelligence and machine learning in their robotics tools. Robots are also used in medicine and education, both in operating rooms and in classrooms.
The number of applications and solutions offered by Machine Learning is enormous. At the same time, we could ensure that the main advantage of machine learning is the ability to sort variables, that is, find and structure data that in some way affects the result. It is for this reason that they are so effective in predicting and determining results, thus helping us to achieve our goals.
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