Basic Elements of Machine Learning
DOI:
https://doi.org/10.22481/intermaths.v4i2.13422Keywords:
Machine Learning (ML), Artificial Intelligence (AI), Educational Data Mining (EDM), School Dropout Prediction, Neural Networks (RN)Abstract
In this work we reviewed six scientific articles on school dropout that used Machine Learning as a methodology to point out the possible causes. The methodology used by this research is bibliographical, because it was investigated what are the themes and technical elements of each of the articles, especially in relation to machine learning. The results obtained are about the main elements that structure the machine learning algorithms from the six scientific articles studied. The theme is very comprehensive and involves several areas and subareas of scientific knowledge, such as Linear Algebra, Matrices, Theory of Computation, Computability, Models of Computation, Formal Language and Automata, Analysis of Algorithms and Computational Complexity. Data Mining Techniques (EDM) are the actions used to find patterns in a large volume of data. These patterns can be explanatory, so as to describe the relationships between data segments, or predictive, which can predict future values based on previous data. At the end, the reader will have a broad view of how the entire methodological process of production and construction of machine learning occurs.
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