Abstract This paper is a methodological guide to using machine learning in the spatial context. It provides an overview of existing toolbox proposed literature: unsupervised learning, which deals with clustering data, and supervised displaces classical econometrics. shows potential this developing methodology, as well its pitfalls. catalogues comments on usage methods (for locations values, bot...

Standard machine-learning approaches involve the centralization of training data in a center, where centralized algorithms can be applied for analysis and inference. However, due to privacy restrictions limited communication resources wireless networks, it is often undesirable or impractical devices transmit parameter sever. One approach mitigate these problems federated learning (FL), which en...

This research investigated the correspondence between a sample of Financial Management textbooks and professional learning expectations synthesized in construct Expectation Use. To this end, conceptual framework developed from on practice was integrated with theoretical perspective commognition analysis mathematics education textbooks. A qualitative content performed narrative end-of-chapter pr...