Extraire le Sens du Texte en Utilisant TF-IDF
Course
424 Learners Already enrolled- Acquérir une maîtrise de la synthèse de textes en calculant les scores TF-ISF.
- Comprendre le concept de tokenisation des phrases et des mots pour l'analyse de texte.
- Comprendre comment supprimer les en-têtes et pieds de page inutiles des données textuelles.
- Identifier et utiliser les N phrases principales dans un corps de texte en fonction de leur importance.
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There are 6 modules in this course
Ce projet se concentre sur la conception et la mise en œuvre d'un résumeur de texte robuste, construit en utilisant Python. En exploitant les capacités du Natural Language Toolkit (NLTK) de Python, les participants acquerront une expérience pratique dans le traitement et l'analyse des données textuelles. Le projet couvre une gamme de techniques NLP essentielles pour la synthèse de texte. Les participants développeront des compétences en analyse de texte et en extraction de contenu significatif, apprenant à filtrer les informations essentielles à partir de grands volumes de texte.- IntroductionPreview
- Importer NLTKPreview
- Charger les Données TextuellesPreview
- Supprimer l'En-tête et le Pied de PagePreview
- Tokeniser les PhrasesPreview
- Tokeniser les MotsPreview
- Score TFPreview
- Fréquence des MotsPreview
- Score ISFPreview
- Score TF-ISFPreview
- Score des PhrasesPreview
- Phrases N PrincipalesPreview
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