MACHINE LEARNING: WELCOME TO THE WORLD OF MACHINES WITH INFINITE LEARNING CAPACITY Technology teaches the computer through training, data analysis and pattern detection, providing large amounts of information to the system, thus generating knowledge Salvador, 01/16/2020 - In 1959, the engineer at MIT - Massachusetts Institute of Technology -, Arthur Samuel, created the term machine learning (MA), and defined it as: “field of study that gives computers the ability to learn without being explicitly programmed ”, translating, the“ field of study that gives computers the ability to learn without being explicitly programmed ”. That said, ML can be translated as machine learning or machine learning: a computational application associated with Artificial Intelligence (AI), which despite gaining more and more prominence in the media, not everyone understands the concept. Many people think that machine learning and AI mean the same thing, but not quite. In fact, AI is a broader technological concept, which includes machine learning, which we treat here, as one of its resources. Thus, ML is one of the artificial intelligence approaches, which aims to teach the computer through training, data analysis, and pattern detection, providing the computer system with a large amount of information to extract knowledge. This technology has evolved a lot, and took shape with the advent of the internet. Because, with the range of information stored on the web, it was necessary to create ways to organize this gigantic content in an automated way - and one of the pillars of machine learning is precisely the analysis of data in order to detect patterns. Many applications that we use today use technology as a means of making the computer intelligent. An example of our daily lives is Netflix. Whoever uses the streaming service must have realized that the more you watch, the more he knows your profile, based on your choices, the system suggests a movie that has great chances of pleasing you. MA also has other learning approaches. One is called deep learning. In it, large amounts of data are treated from several layers of artificial neural networks (algorithms inspired by the structure of neurons in the brain), which solve complex problems, such as object recognition in images. Infinite learning ability InfoStore Group CEO, Pedro Henrique Mussi de Amorim Brandão explains that machine learning has infinite learning capacity. "It is important to emphasize that the assertiveness and enormous capacity to learn of this application is proportional to the number of times that it has been trained", highlights Pedro Mussi.
In the final stage of development, using Machine Learning and Artificial Neural Networks, the Server X-Ray software has access to a daily load of processes sent to the customer's server, analyzing this data and classifying processes through prior knowledge, developing an experience, that evolves towards the acquisition of knowledge and learning. “Our challenge is to create a server performance management and optimization system, which aims to serve from a small business to a data center. For this, we use AI, more specifically a machine learning, which analyzes requests to the server, compares the tasks sent and classifies them in order of priority”, explains Mussi. Uses of machine learning The use of machine learning in the most diverse applications only tends to grow. It is not by whim, but by necessity: many technological resources that we have today only work or are viable because of artificial intelligence. Here are some examples: Autonomous database: with the aid of machine learning, autonomous databases automatically deal with various tasks previously performed by an administrator (DBA), allowing the professional to take care of other activities and reducing the risk of application unavailability due to failure human; Fight fraud in payment systems: several attempts at credit card fraud are generated every second; however, machine learning has allowed fraud-fighting systems to stop most of these actions; Text translation: a translation can never be done literally; because it is necessary to take into account contexts, regional expressions and other parameters. Thanks to machine learning, machine translators are becoming more and more accurate; Content recommendation: video and audio streaming platforms use the MA to analyze the history of content played or rejected by the user to offer recommendations compatible with their tastes. Big Data and Machine Learning In recent times, the business world has witnessed the union of Big Data and machine learning tools, in order to enable even more strategic performance by companies through investment in technology. In practice, this combination, which combines machine learning and the processing of large amounts of data, is capable of bringing a number of benefits to organizations. Big Data is a term used in the field of Information Technology that refers to the large set of data (structured or not). The term is used to describe the process of analysis, processing and strategic use of existing data. Enabling the use of this complex information to generate insights and base strategic decisions, for example. One of the most common uses of the combination of Big Data and machine learning is predictive analysis, which consists of using data and machine learning techniques to determine the likelihood of future results based on prior information. By using algorithms and a mathematical language, data science can create transformative solutions for businesses. Using predictive analytics, big data and associated machine learning allow you to outline strategies, optimize actions, interact with customers and, of course, boost sales.
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