April 2026
Intermediate
586 pages
17h 40m
French
Content preview from Apprendre AutoML (French Edition)
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Chapitre 8. AutoML pour le traitement du texte et du langage naturel
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Je me souviens encore de la première fois où j’ai vu un modèle d’apprentissage automatique « comprendre » le langage humain. C’était en 2017, et je travaillais pour un détaillant submergé de tickets d’assistance. Il disposait de centaines de milliers de messages texte non structurés provenant de clients — plaintes, questions, compliments et tout le reste — qui devaient être automatiquement classés et acheminés vers les bonnes équipes.
À l'époque, la mise en place d'un système efficace de classification de texte nécessitait des semaines de travail manuel d'ingénierie des caractéristiques : extraction de n-grammes, calcul des scores TF-IDF, gestion du stemming et de la lemmatisation, et réglage minutieux des pipelines de prétraitement. Le processus était fastidieux et source d'erreurs, et exigeait une expertise approfondie tant en traitement du langage naturel que dans le domaine spécifique.
Aujourd’hui, l’AutoML a radicalement transformé notre approche du traitement de texte. Ce qui nécessitait autrefois une équipe de spécialistes en TALN et des semaines de développement peut désormais être réalisé par un expert du domaine en quelques lignes de code. Dans ce chapitre, on va découvrir comment le MultiModalPredictor d’ -AutoGluon rend des capacités sophistiquées de TALN accessibles ...
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