May 2020
Intermediate to advanced
576 pages
26h 55m
French
Content preview from Deep Learning avec Keras et TensorFlow
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334
Chapitre 9. Apprentissage de représentations et apprentissage génératif
Sorties
(≈ entré es)
Représentation
latente
Entrées
Décodeur
Encodeur
x’
1
x’
2
x’
3
x
1
x
2
x
3
Figure 9.1 – Expérience de mémorisation dans les échecs (à gauche)
et autoencodeur simple (à droite)
Un autoencodeur possède généralement la même architecture qu’un perceptron
multicouche (PMC ; voir le chapitre2), mais le nombre de neurones de la couche
de sortie doit être égal au nombre d’entrées. Dans l’exemple illustré, nous avons une
seule couche cachée constituée de deux neurones (l’encodeur) et une couche de
sortie constituée de trois neurones (le décodeur). Les sorties sont souvent ...
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