Mostrando ítems 1-10 de 1063
Machine Learning e ensino individualizado na Matemática: uma ferramenta para o professor
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Ensino de Ciências Exatas - PPGECECâmpus São Carlos, 2021-07-02)
This research aims to investigate how the use of Machine Learning can contribute to the teacher in the identification of the mathematical skills of the students of the three years of High School for individualized teaching ...
On the training algorithms for Restricted Boltzmann Machine-Based Models
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Ciência da Computação - PPGCCCâmpus São Carlos, 2018-12-05)
Deep learning techniques have been studied extensively in the last years, due to its good results related to essential tasks on a large range of applications, such as speech and face recognition, as well as objects ...
Comparativo de alguns modelos de machine learning utilizando dados de domínio público e a linguagem python
(Universidade Estadual Paulista (Unesp), 2021-08-27)
There are many applications of machine learning models in various areas, and it is an area of research with continuous development. This work proposes a study of 5 classifier models with supervised learning. Using the ...
Modelo predictivo del movimiento mina utilizando Machine Learning en mina Los Bronces - Anglo American
(Universidad de Chile, 2022)
Curriculum learning applied to the combined algorithm selection and hyperparameter optimization problem
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Ciência da Computação - PPGCCCâmpus São Carlos, 2021-05-25)
AutoML has the goal to find the best Machine Learning (ML) pipeline in a complex and high dimensional search space by evaluating multiple algorithm configurations. Training multiple ML algorithms is time costly, and as ...
Aprendiendo a picar rocas con Deep Reinforcement Learning
(Universidad de Chile, 2022)
Machine learning quantum error correction codes: learning the toric code
(Universidade Estadual Paulista (Unesp), 2018-12-14)
Usamos métodos de aprendizagem supervisionada para estudar a decodificação de erros em códigos tóricos de diferentes tamanhos. Estudamos múltiplos modelos de erro, e obtemos figuras da eficácia de decodificação como uma função ...