Uso de Machine Learn para classificação de lançamentos financeiro: estudo comparativo entre modelo AutoML e Redes MLP

Abstract

The study of this work aims to help companies in their financial management by generating models based on Machine Learning to classify financial releases. With the help of libraries developed in the Python language, it was possible to train AutoML models and Multilayer Perceptron Neural Networks responsible for data classification. With results above 85% in the metrics of Accuracy, Recall, F-measure and Precision for both models, using them brings the possibility of better management of financial releases with less effort.