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Generic data modeling based on the Markov chain theory part of an AutoML system: customizable library and visualization tool
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| 4.45 MB | Adobe PDF |
Orientador(es)
Resumo(s)
Artificial Intelligence and automation have significantly expanded as a research field, and gradually
play an increasingly important role in business decision-making. The goal of this internship is to
implement a highly customizable library as part of an Automated Machine Learning system, which
intends to give accessibility of data-driven decisions to less experienced users, and let them perform
in-depth analyzes on large quantities of data. This library is built upon the Markov chain theory,
which has several real-world applications and also serves as the basis for other theories with a higher
level of complexity. In addition to the library, a visualization tool is also conceived to facilitate the use
of the library by providing an interface to process parameter settings and display modeling data in
the form of interactive directed graphs.
Descrição
Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
Palavras-chave
Artificial Intelligence Automated Machine Learning Markov Chain Directed Graph Visualization