August 2026
Intermediate
548 pages
18h 47m
French
Content preview from Ingénierie des données pour l'IA multimodale (French Edition)
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Chapitre 7. Flux en continu et pipelines adaptatifs pour l’IA multimodale
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La plupart d’entre nous ont appris à considérer les pipelines de streaming comme des flots de données homogènes. On pense aux flux de clics, aux données de capteurs ou aux événements de trading qui arrivent dans un ordre chronologique strict. Il suffit d’ajouter un sérialiseur, de partitionner par clé, de passer par un courtier de messages, et le traitement des données est alors largement procédural.
Le streaming multimodal bouleverse cette zone de confort. Un pipeline multimodal doit synchroniser la sémantique entre des horloges qui n’ont rien en commun. Ton système peut très bien traiter une image vidéo de drone toutes les 33 millisecondes, une sonde d’humidité du sol toutes les 5 secondes, une mesure de rafale de vent uniquement lorsque des seuils sont franchis, et une commande d’apprentissage automatique qui arrive sur une boucle de contrôle complètement différente. Le défi de l’ingénierie des données consiste à fusionner ces données asynchrones en une seule surface de décision cohérente dans le temps. C’est à relever ce défi que ce chapitre est consacré.
Pour rendre ces défis concrets, on va suivre FieldSense, une entreprise fictive d’agriculture de précision inspirée du secteur, qui fait voler des drones multispectraux au-dessus de cultures en rangs tandis que des appareils ...
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