Traitement de données avant un entrainement de modèle avec Tensorflow
Création d'un modèle de Deep Learning avec une couche Embedding
Extraire et visualiser les poids d'une couche Embedding
Dans ce projet guidé, vous créerez un modèle de Machine Learning d’analyse de sentiments par classification de textes avec Tensorflow, en utilisant le plongement de mots (Word Embedding). Vous allez vous exercer avec des données collectées sur le site www.allocine.fr Le word embedding est une méthode d'apprentissage d'une représentation de mots utilisée traitement automatique des langues. Il donne d’excellents résultats comme vous pourrez le constater dans ce projet guidé. Ce cours est destiné aux ingénieurs en Machine Learning, au Data Scientists et tous les curieux désireux d’apprendre à faire de la classification de textes facilement.
Deep Learning
Word Embedding
Tensorflow
Programmation Python
Classification de Texte
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction & Installations
Préparation des données (3 vidéos)
Rembourrage et théorie Word Embedding
Création du modèle avec une couche Embedding
Entrainement du modèle
Évaluation du modèle
Visualisation du Word Embedding appris
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In a split-screen video, your instructor guides you step-by-step
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