Machine learning is a form of artificial intelligence that allows an automated system to be able to “learn” from experience.
We are facing a world that is improving by leaps and bounds, which makes it increasingly complex to understand. In the last five years, more information has been generated than has ever been created by mankind in its entire history due to the amount of scientific research developed in different disciplines, in addition to the data originated from climatic and atmospheric information sensors, satellite observation data, and even data generated by millions of people on a daily basis from their interaction with computers and advanced information systems.
Given the large amount of information that is available for almost anything, as well as data that reflect trends, activities or repetitive behaviors, it is possible to optimize them through the application of machine learning algorithms. All this allows the development of tools that guarantee organizations an adequate management of the information and with an adequate identification of patterns and trends, models can be generated that allow them to make timely, immediate and profitable decisions.
In this context, we find that Machine Learning techniques are more relevant than ever, as they contribute to the organization and identification of available data, help us to easily find the relationships between different variables within a process, reduce the margin of error in the estimation of a result, among others. Likewise, it can be applied in fields such as scientific research, medicine, financial activities, industry, exploitation and pollution control from the analysis of satellite images.
