Master's student in Engineering, Large-Scale Data Mining, and Data Science at the University of São Paulo. Bachelor's degree in Computer Science from UFSCar. Experience in Scientific Initiation research projects supported by FAPESP scholarship in time series classification using meta-learning. Nine months of experience as a programmer in the Bug Fix team at Luz Soluções Financeiras. Technical background in Informatics from ETEC. Four months of international exchange experience in England. (Source: Lattes Curriculum)
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Due to the increasing collection of overtime observed data, time series are becoming a ubiquitous type of data in human beings' daily lives. This fact has also caused a significant increase in the number of techniques for time series classification in recent decades. In this scenario, when a researcher or developer needs a solution based on a classification model, there is a wide range of…
Time series data is becoming ubiquitous in our everyday tasks. The increasing collection of data observed over time has also increased the number of techniques for classifying time series. In this scenario, when a researcher or practitioner needs a classification solution, there is a vast range of options of algorithms to apply. When only one algorithm is chosen, its performance may not a…
| 1 / 1 | Completed scholarships in Brazil |
| 1 / 1 | Completed scholarships abroad |
| 2 / 2 | All Scholarships |
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