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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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Don't let this gap widen
Sans maîtrise de TensorFlow, 85 % des projets Deep Learning échouent en phase d'implémentation, gaspillant en moyenne 6 mois de développement et 250 000 € par initiative ratée.
Les data teams perdent 40 % de productivité en debugging incessant, exposant l'entreprise à des incidents en production multipliés par 3.
Votre compétitivité s'effondre face aux rivaux agiles, tandis que votre carrière patine dans un marché où 70 % des postes data exigent une expertise TensorFlow avancée.
Chaque mois d'inaction creuse le fossé financier et stratégique.
The Maîtriser TensorFlow : de la prise en main à l’application pratique du Deep Learning training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Maîtriser TensorFlow : de la prise en main à l’application pratique du Deep Learning training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Maîtriser TensorFlow : de la prise en main à l’application pratique du Deep Learning training is carried out through:
Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Historique et cas d’usages du Deep Learning. Présentation de TensorFlow et installation. Compréhension de la philosophie TensorFlow (Graph, Sessions, Tensors). Utilisation de Google Colab et environnement de travail. Premier modèle simple de régression linéaire avec TensorFlow.
Présentation de l’API Keras intégrée à TensorFlow. Conception d’un MLP (Multi-Layer Perceptron) pour la classification d’images (jeu de données MNIST). Préparation des données : chargement, normalisation, repartition. Entraînement, validation croisée et surapprentissage. Monitoring des performances avec TensorBoard.
Fonctionnalités avancées : callbacks, sauvegarde et restauration de modèles, transfert d’apprentissage. Optimisation des performances et tuning d’hyperparamètres. Export et déploiement de modèles (TF Serving, TFLite). Introduction au traitement d’images et de textes. Étude de cas complète sur un projet réel, de la préparation des données au déploiement.
Target audience
Développeurs, data scientists, ingénieurs et chercheurs souhaitant se familiariser avec TensorFlow pour le Deep Learning
Prerequisites
Bonne compréhension de Python et connaissances de base en machine learning
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