May 2020
Intermediate to advanced
576 pages
26h 55m
French
Content preview from Deep Learning avec Keras et TensorFlow
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154
Chapitre 4. Modèles personnalisés et entraînement avec TensorFlow
de caractères, et pour les conversions de l’une à l’autre. Il est important de
noter qu’un tf.string est atomique, c’est-à-dire que sa longueur n’apparaît
pas dans la forme du tenseur. Après qu’il a été converti en un tenseur Unicode
(autrement dit, un tenseur de type tf.int32 contenant des points de code),
la longueur est présente dans la forme.
•
Ensembles
Ils sont représentés sous forme de tenseurs normaux (ou tenseurs creux).
Par exemple, tf.constant([[1, 2], [3, 4]]) représente les deux
ensembles {1, 2} et {3, 4}. Plus généralement, chaque ensemble est représenté
par un ...
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