March 2019
Intermediate to advanced
576 pages
20h 51m
Portuguese (Portugal, Brazil)
Content preview from Mãos à Obra: Aprendizado de Máquina com Scikit-Learn e TensorFlow
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Soluções dos Exercícios | 513
camada convolucional também possui kernels 3 × 3 e sua entrada é o conjunto de
200 mapas das camadas anteriores, portanto cada mapa de características tem pe-
sos 3 × 3 × 200 = 1.800, além de um termo de polarização. Como possui 400 mapas,
essa camada tem um total de 1.801 × 400 = 720.400 parâmetros. Ao todo, a CNN
tem 2.800 + 180.200 + 720.400 = 903.400 parâmetros.
Agora, calcularemos a quantidade de memória RAM que essa rede neural exigirá
(pelo menos) ao fazer uma previsão para uma única instância. Primeiro, calcula-
remos o tamanho do mapa de características para cada camada e, como estamos
usando um incremen ...
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