October 2018
Intermediate to advanced
260 pages
7h 2m
French
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CHAPITRE 5 Optimiser les hyperparamètres
Entraîner un modèle profond et entraîner un bon modèle profond sont des choses très différentes. Bien qu’il soit assez facile de copier/coller du code TensorFlow récupéré sur Internet pour faire fonctionner un premier prototype, il est beaucoup plus difficile de transformer ce prototype en un modèle de haute qualité. Cette transformation implique de nombreuses étapes. Dans ce chapitre, nous allons explorer l’une de ces étapes, qui concerne l’optimisation des hyperparamètres.
En première approximation, l’optimisation des hyperparamètres est le processus qui consiste à mettre au point tous les paramètres d’un modèle qui ne sont pas appris par la descente du gradient. Ce sont ces quantités qui sont appelées ...
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