{"title":"Frameworks de ML\/DL","description":"\u003ch3 data-end=\"321\" data-start=\"286\"\u003eQu'est-ce que les frameworks de ML\/DL ?\u003c\/h3\u003e\n\u003cp data-end=\"703\" data-start=\"322\"\u003e\u003cstrong data-end=\"347\" data-start=\"322\"\u003eLe ML (apprentissage automatique)\u003c\/strong\u003e et \u003cstrong data-end=\"374\" data-start=\"352\"\u003ele DL (apprentissage profond)\u003c\/strong\u003e sont des bibliothèques logicielles ou des plateformes qui aident les développeurs à créer, entraîner et déployer des modèles d'IA plus facilement.\u003c\/p\u003e\n\u003cp data-end=\"1405\" data-start=\"1325\"\u003e📚 \u003cstrong data-end=\"1360\" data-start=\"1328\"\u003eTraitement du langage et du texte\u003c\/strong\u003e – traduction, chatbots, analyse de sentiment\u003c\/p\u003e\n\u003cp data-end=\"1477\" data-start=\"1408\"\u003e📈 \u003cstrong data-end=\"1432\" data-start=\"1411\"\u003eModèles de prédiction\u003c\/strong\u003e – prévisions en finance, énergie, logistique\u003c\/p\u003e\n\u003cp data-end=\"1557\" data-start=\"1480\"\u003e🧪 \u003cstrong data-end=\"1510\" data-start=\"1483\"\u003eRecherche \u0026amp; prototypage\u003c\/strong\u003e – développement de nouveaux algorithmes ou modèles\u003c\/p\u003e\n\u003cp data-end=\"1647\" data-start=\"1560\"\u003e🌐 \u003cstrong data-end=\"1590\" data-start=\"1563\"\u003eDéploiements en production\u003c\/strong\u003e – intégration de modèles entraînés dans des applications réelles\u003c\/p\u003e","products":[{"product_id":"tensorflow-open-source-machine-learning-plattform-fur-entwickler-🗺️","title":"TensorFlow – Plateforme d'apprentissage automatique open source pour les développeurs 🪴","description":"\u003ch3 data-start=\"211\" data-end=\"237\"\u003e🧠 Qu'est-ce que TensorFlow ?\u003c\/h3\u003e\n\u003cp data-start=\"239\" data-end=\"617\"\u003eTensorFlow est une bibliothèque logicielle open source dédiée au machine learning, développée par l'équipe Google Brain. Elle sert à concevoir des algorithmes complexes, à entraîner des réseaux de neurones et à déployer des modèles pour des prédictions et des analyses. TensorFlow fonctionne sur diverses plateformes, des serveurs aux appareils mobiles en passant par l'edge computing. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.tensorflow.org\/about?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.tensorflow.org\/about?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eTensorFlow\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eWikipedia\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003chr data-start=\"619\" data-end=\"622\"\u003e\n\u003ch3 data-start=\"624\" data-end=\"658\"\u003e🌟 Avantages et spécificités\u003c\/h3\u003e\n\u003cul data-start=\"660\" data-end=\"1389\"\u003e\n\n\u003cli data-start=\"660\" data-end=\"831\"\u003e\n\n\u003cp data-start=\"662\" data-end=\"831\"\u003e\u003cstrong data-start=\"662\" data-end=\"683\"\u003eGrande flexibilité\u003c\/strong\u003e – TensorFlow propose des interfaces simples comme Keras pour les débutants, ainsi que des API de bas niveau pour les besoins spécifiques. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.tensorflow.org\/about?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.tensorflow.org\/about?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eTensorFlow\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"832\" data-end=\"974\"\u003e\n\n\u003cp data-start=\"834\" data-end=\"974\"\u003e\u003cstrong data-start=\"834\" data-end=\"878\"\u003eVaste communauté d'utilisateurs et de développeurs\u003c\/strong\u003e – Sa licence open source permet à un grand nombre de contributeurs d'y participer. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/en.wikipedia.org\/wiki\/TensorFlow?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/en.wikipedia.org\/wiki\/TensorFlow?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eWikipedia\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"975\" data-end=\"1101\"\u003e\n\n\u003cp data-start=\"977\" data-end=\"1101\"\u003e\u003cstrong data-start=\"977\" data-end=\"1000\"\u003eMultiplateforme\u003c\/strong\u003e – Fonctionne sur CPU, GPU, appareils mobiles et même sur le web. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.nvidia.com\/en-us\/glossary\/tensorflow\/?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.nvidia.com\/en-us\/glossary\/tensorflow\/?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eNVIDIA\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eTechRadar\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1102\" data-end=\"1255\"\u003e\n\n\u003cp data-start=\"1104\" data-end=\"1255\"\u003e\u003cstrong data-start=\"1104\" data-end=\"1131\"\u003ePrêt pour la production\u003c\/strong\u003e – Les modèles sont facilement scalables et déployables, avec la possibilité d'effectuer des inférences via TensorFlow Serving. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.tensorflow.org\/tfx\/guide\/serving?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.tensorflow.org\/tfx\/guide\/serving?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eTensorFlow\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eTensorFlow\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1256\" data-end=\"1389\"\u003e\n\n\u003cp data-start=\"1258\" data-end=\"1389\"\u003e\u003cstrong data-start=\"1258\" data-end=\"1280\"\u003eUtilisation gratuite\u003c\/strong\u003e – La licence Apache 2.0 autorise l'utilisation, la modification et la distribution libres. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/en.wikipedia.org\/wiki\/TensorFlow?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/en.wikipedia.org\/wiki\/TensorFlow?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eWikipedia\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003chr data-start=\"1391\" data-end=\"1394\"\u003e\n\u003ch3 data-start=\"1396\" data-end=\"1419\"\u003e🧭 Vision et valeurs\u003c\/h3\u003e\n\u003cp data-start=\"1421\" data-end=\"1638\"\u003eTensorFlow vise à rendre le machine learning accessible à tous : chercheurs, développeurs et créatifs. L'objectif est de stimuler l'innovation, d'accélérer la recherche et de permettre des solutions qui répondent à des problèmes réels 🌍💡.\u003c\/p\u003e\n\u003chr data-start=\"1640\" data-end=\"1643\"\u003e\n\u003ch2 data-start=\"1645\" data-end=\"1670\"\u003e📦 Organisation du produit\u003c\/h2\u003e\n\u003cul data-start=\"1672\" data-end=\"2096\"\u003e\n\n\u003cli data-start=\"1672\" data-end=\"1733\"\u003e\n\n\u003cp data-start=\"1674\" data-end=\"1733\"\u003e\u003cstrong data-start=\"1674\" data-end=\"1694\"\u003eCatégorie de produit\u003c\/strong\u003e : Bibliothèque logicielle de machine learning\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1734\" data-end=\"1813\"\u003e\n\n\u003cp data-start=\"1736\" data-end=\"1813\"\u003e\u003cstrong data-start=\"1736\" data-end=\"1750\"\u003eType de produit\u003c\/strong\u003e : Framework open source, bibliothèque d'entraînement et d'inférence\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1814\" data-end=\"1853\"\u003e\n\n\u003cp data-start=\"1816\" data-end=\"1853\"\u003e\u003cstrong data-start=\"1816\" data-end=\"1828\"\u003eFournisseur\u003c\/strong\u003e : Google Brain (Google)\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1854\" data-end=\"1982\"\u003e\n\n\u003cp data-start=\"1856\" data-end=\"1982\"\u003e\u003cstrong data-start=\"1856\" data-end=\"1873\"\u003eLignes de produits\u003c\/strong\u003e : API Keras, TensorFlow Lite (mobile\/edge), TensorFlow.js (web), TensorFlow Serving (déploiement en production)\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1983\" data-end=\"2096\"\u003e\n\n\u003cp data-start=\"1985\" data-end=\"2096\"\u003e\u003cstrong data-start=\"1985\" data-end=\"2003\"\u003eTags pertinents\u003c\/strong\u003e : #MachineLearning 🤖 #DeepLearning #OpenSource 🌱 #IA #RéseauxDeNeurones #Entraînement #Inférence\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003chr data-start=\"2098\" data-end=\"2101\"\u003e\n\u003ch2 data-start=\"2103\" data-end=\"2128\"\u003e🧰 Exemples d'applications\u003c\/h2\u003e\n\u003cul data-start=\"2130\" data-end=\"2413\"\u003e\n\n\u003cli data-start=\"2130\" data-end=\"2201\"\u003e\n\n\u003cp data-start=\"2132\" data-end=\"2201\"\u003eReconnaissance d'images, traitement de la parole, traitement du langage naturel\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2202\" data-end=\"2262\"\u003e\n\n\u003cp data-start=\"2204\" data-end=\"2262\"\u003eModèles de prédiction pour l'analyse de données, la recherche et l'industrie\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2263\" data-end=\"2309\"\u003e\n\n\u003cp data-start=\"2265\" data-end=\"2309\"\u003eApplications mobiles avec inférence embarquée (on-device)\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2310\" data-end=\"2350\"\u003e\n\n\u003cp data-start=\"2312\" data-end=\"2350\"\u003eApplications web avec intégration de modèles\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2351\" data-end=\"2413\"\u003e\n\n\u003cp data-start=\"2353\" data-end=\"2413\"\u003eExpériences de recherche, prototypage, déploiements en production\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e","brand":"Antus","offers":[{"title":"Default Title","offer_id":53595635908940,"sku":null,"price":1.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0933\/9011\/1052\/files\/TensorFlow_Open-Source_Machine_Learning_Plattform_f_r_Entwickler.png?v=1760389317"},{"product_id":"keras-intuitive-deep-learning-bibliothek-fur-entwickler-und-forschung-🌎","title":"Keras – Bibliothèque de deep learning intuitive pour les développeurs et la recherche 🌎","description":"\u003ch3 data-start=\"189\" data-end=\"210\"\u003e🧠 Qu'est-ce que Keras ?\u003c\/h3\u003e\n\u003cp data-start=\"212\" data-end=\"662\"\u003eKeras est une bibliothèque open source dédiée au deep learning, écrite en Python. Elle fournit une API de haut niveau qui simplifie considérablement pour les développeurs la construction, l'entraînement et le déploiement de réseaux de neurones 🛠️. Keras fonctionne avec divers moteurs backend tels que TensorFlow, Theano ou, par le passé, CNTK. Depuis la version 3, Keras s'appuie principalement sur plusieurs frameworks modernes comme TensorFlow, JAX et PyTorch en tant que backend. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/keras.io\/getting_started\/about\/?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/keras.io\/getting_started\/about\/?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003ekeras.io\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003ekeras.io\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003chr data-start=\"664\" data-end=\"667\"\u003e\n\u003ch3 data-start=\"669\" data-end=\"703\"\u003e🌟 Avantages et particularités\u003c\/h3\u003e\n\u003cul data-start=\"705\" data-end=\"1444\"\u003e\n\n\u003cli data-start=\"705\" data-end=\"828\"\u003e\n\n\u003cp data-start=\"707\" data-end=\"828\"\u003e\u003cstrong data-start=\"707\" data-end=\"741\"\u003eFacile à comprendre et à lire\u003c\/strong\u003e – Le code semble simple, propre et facile à maintenir. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/keras.io\/?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/keras.io\/?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003ekeras.io\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"829\" data-end=\"962\"\u003e\n\n\u003cp data-start=\"831\" data-end=\"962\"\u003e\u003cstrong data-start=\"831\" data-end=\"862\"\u003ePrototypage rapide possible\u003c\/strong\u003e – Les modèles peuvent être configurés, testés et adaptés rapidement. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/blog.tensorflow.org\/2018\/12\/standardizing-on-keras-guidance.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/blog.tensorflow.org\/2018\/12\/standardizing-on-keras-guidance.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eblog.tensorflow.org\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"963\" data-end=\"1129\"\u003e\n\n\u003cp data-start=\"965\" data-end=\"1129\"\u003e\u003cstrong data-start=\"965\" data-end=\"980\"\u003eModularité\u003c\/strong\u003e – Les composants peuvent être réutilisés, combinés, et il est possible de créer ses propres couches ou fonctions de perte. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/keras.io\/?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/keras.io\/?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003ekeras.io\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1130\" data-end=\"1285\"\u003e\n\n\u003cp data-start=\"1132\" data-end=\"1285\"\u003e\u003cstrong data-start=\"1132\" data-end=\"1165\"\u003eSupport multi-framework\u003c\/strong\u003e – Keras 3 permet d'utiliser les backends TensorFlow, JAX ou PyTorch selon les besoins. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/keras.io\/getting_started\/about\/?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/keras.io\/getting_started\/about\/?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between overflow-hidden\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003ekeras.io\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1286\" data-end=\"1444\"\u003e\n\n\u003cp data-start=\"1288\" data-end=\"1444\"\u003e\u003cstrong data-start=\"1288\" data-end=\"1323\"\u003eLarge communauté et adoption\u003c\/strong\u003e – Keras est souvent utilisé dans la recherche, l'enseignement ainsi que dans des projets de production. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.ionos.de\/digitalguide\/online-marketing\/suchmaschinenmarketing\/was-ist-keras\/?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.ionos.de\/digitalguide\/online-marketing\/suchmaschinenmarketing\/was-ist-keras\/?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eIONOS\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003chr data-start=\"1446\" data-end=\"1449\"\u003e\n\u003ch3 data-start=\"1451\" data-end=\"1474\"\u003e🧭 Vision et valeurs\u003c\/h3\u003e\n\u003cp data-start=\"1476\" data-end=\"1741\"\u003eKeras souhaite rendre le machine learning accessible à tous – les débutants comme les chercheurs doivent pouvoir démarrer rapidement sans avoir à comprendre des détails complexes de bas niveau. L'accent est mis sur la clarté, la flexibilité et la meilleure expérience utilisateur possible 💡.\u003c\/p\u003e\n\u003chr data-start=\"1743\" data-end=\"1746\"\u003e\n\u003ch2 data-start=\"1748\" data-end=\"1773\"\u003e📦 Organisation du produit\u003c\/h2\u003e\n\u003cul data-start=\"1775\" data-end=\"2246\"\u003e\n\n\u003cli data-start=\"1775\" data-end=\"1848\"\u003e\n\n\u003cp data-start=\"1777\" data-end=\"1848\"\u003e\u003cstrong data-start=\"1777\" data-end=\"1797\"\u003eCatégorie de produit\u003c\/strong\u003e : Bibliothèque de deep learning, outil de machine learning\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1849\" data-end=\"1905\"\u003e\n\n\u003cp data-start=\"1851\" data-end=\"1905\"\u003e\u003cstrong data-start=\"1851\" data-end=\"1865\"\u003eType de produit\u003c\/strong\u003e : API de haut niveau, logiciel open source\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1906\" data-end=\"2021\"\u003e\n\n\u003cp data-start=\"1908\" data-end=\"2021\"\u003e\u003cstrong data-start=\"1908\" data-end=\"1920\"\u003eFournisseur\u003c\/strong\u003e : Projet open source initié par François Chollet, maintenu par la communauté et l'équipe TensorFlow\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2022\" data-end=\"2144\"\u003e\n\n\u003cp data-start=\"2024\" data-end=\"2144\"\u003e\u003cstrong data-start=\"2024\" data-end=\"2055\"\u003eLignes de produits \/ composants\u003c\/strong\u003e : Keras Core API, Keras Layers, sous-classement de modèles, support de divers backends\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2145\" data-end=\"2246\"\u003e\n\n\u003cp data-start=\"2147\" data-end=\"2246\"\u003e\u003cstrong data-start=\"2147\" data-end=\"2165\"\u003eTags pertinents\u003c\/strong\u003e : #DeepLearning 🤖 #MachineLearning #OpenSource 🌱 #Keras #Python #Modélisation 🧱\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003chr data-start=\"2248\" data-end=\"2251\"\u003e\n\u003ch2 data-start=\"2253\" data-end=\"2278\"\u003e🧰 Exemples d'applications\u003c\/h2\u003e\n\u003cul data-start=\"2280\" data-end=\"2578\"\u003e\n\n\u003cli data-start=\"2280\" data-end=\"2353\"\u003e\n\n\u003cp data-start=\"2282\" data-end=\"2353\"\u003eReconnaissance d'images, segmentation, détection d'objets pour des projets de vision 🖼️\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2354\" data-end=\"2426\"\u003e\n\n\u003cp data-start=\"2356\" data-end=\"2426\"\u003eTraitement du langage naturel, traduction, classification de texte 📚\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2427\" data-end=\"2511\"\u003e\n\n\u003cp data-start=\"2429\" data-end=\"2511\"\u003eRecherche et enseignement – développer, comparer et publier des modèles de manière expérimentale\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2512\" data-end=\"2578\"\u003e\n\n\u003cp data-start=\"2514\" data-end=\"2578\"\u003eInférence mobile ou Edge, déploiements web avec des modèles Keras\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e","brand":"Antus","offers":[{"title":"Default Title","offer_id":53595727069516,"sku":null,"price":1.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0933\/9011\/1052\/files\/Keras_ist_eine_Open-Source_Bibliothek_f_r_Deep_Learning.png?v=1760390023"},{"product_id":"scikit-learn-die-bewahrte-machine-learning-bibliothek-fur-python","title":"Scikit-learn – La bibliothèque de machine learning éprouvée pour Python 🧠","description":"\u003ch3 data-start=\"214\" data-end=\"244\"\u003e🧠 Qu'est-ce que scikit-learn ?\u003c\/h3\u003e\n\u003cp data-start=\"246\" data-end=\"634\"\u003e\u003cstrong data-start=\"246\" data-end=\"262\"\u003escikit-learn\u003c\/strong\u003e est une bibliothèque open source populaire pour l'apprentissage automatique en Python. Elle offre des interfaces simples et uniformes pour de nombreux algorithmes standard tels que la classification, la régression, le clustering et la réduction de dimension. La bibliothèque s'appuie sur NumPy et SciPy et est utilisée dans le monde entier dans la recherche, l'enseignement et l'industrie. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/scikit-learn.org\/?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/scikit-learn.org\/?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eScikit-learn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eWikipedia\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003chr data-start=\"636\" data-end=\"639\"\u003e\n\u003ch3 data-start=\"641\" data-end=\"677\"\u003e🌟 Avantages et particularités\u003c\/h3\u003e\n\u003cul data-start=\"679\" data-end=\"1379\"\u003e\n\n\u003cli data-start=\"679\" data-end=\"808\"\u003e\n\n\u003cp data-start=\"681\" data-end=\"808\"\u003e\u003cstrong data-start=\"681\" data-end=\"703\"\u003eFacilité d'utilisation\u003c\/strong\u003e – une API identique pour de nombreux algorithmes permet une prise en main rapide \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.ibm.com\/think\/topics\/scikit-learn?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.ibm.com\/think\/topics\/scikit-learn?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eIBM\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eDigitalOcean\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"809\" data-end=\"961\"\u003e\n\n\u003cp data-start=\"811\" data-end=\"961\"\u003e\u003cstrong data-start=\"811\" data-end=\"846\"\u003eLarge éventail d'algorithmes\u003c\/strong\u003e – par ex. Random Forest, machines à vecteurs de support (SVM), K-Means, Gradient Boosting \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/en.wikipedia.org\/wiki\/Scikit-learn?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/en.wikipedia.org\/wiki\/Scikit-learn?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eWikipedia\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eDigitalOcean\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"962\" data-end=\"1085\"\u003e\n\n\u003cp data-start=\"964\" data-end=\"1085\"\u003e\u003cstrong data-start=\"964\" data-end=\"998\"\u003eUtilisation gratuite sous licence BSD\u003c\/strong\u003e – autorise l'usage commercial et les modifications \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/github.com\/scikit-learn\/scikit-learn?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/github.com\/scikit-learn\/scikit-learn?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eWikipedia\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+3\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eGitHub\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+3\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eScikit-learn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+3\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1086\" data-end=\"1212\"\u003e\n\n\u003cp data-start=\"1088\" data-end=\"1212\"\u003e\u003cstrong data-start=\"1088\" data-end=\"1117\"\u003eCommunauté active \u0026amp; maintenance\u003c\/strong\u003e – nombreuses contributions, mises à jour régulières, écosystème robuste \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/github.com\/scikit-learn\/scikit-learn?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/github.com\/scikit-learn\/scikit-learn?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eGitHub\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eScikit-learn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1213\" data-end=\"1379\"\u003e\n\n\u003cp data-start=\"1215\" data-end=\"1379\"\u003e\u003cstrong data-start=\"1215\" data-end=\"1258\"\u003eScalabilité pour des jeux de données moyens\u003c\/strong\u003e – idéal pour les tâches classiques de ML, moins pour les modèles de deep learning très complexes \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.digitalocean.com\/community\/tutorials\/python-scikit-learn-tutorial?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.digitalocean.com\/community\/tutorials\/python-scikit-learn-tutorial?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eDigitalOcean\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eWikipedia\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003chr data-start=\"1381\" data-end=\"1384\"\u003e\n\u003ch3 data-start=\"1386\" data-end=\"1411\"\u003e🧭 Vision et valeurs\u003c\/h3\u003e\n\u003cp data-start=\"1413\" data-end=\"1634\"\u003escikit-learn vise à rendre l'apprentissage automatique accessible, stable et fiable. Grâce à sa simplicité et sa cohérence, la bibliothèque permet de se concentrer sur les modèles et les analyses plutôt que sur le code répétitif.\u003c\/p\u003e\n\u003chr data-start=\"1636\" data-end=\"1639\"\u003e\n\u003ch2 data-start=\"1641\" data-end=\"1668\"\u003e📦 Organisation du produit\u003c\/h2\u003e\n\u003cul data-start=\"1670\" data-end=\"2230\"\u003e\n\n\u003cli data-start=\"1670\" data-end=\"1735\"\u003e\n\n\u003cp data-start=\"1672\" data-end=\"1735\"\u003e\u003cstrong data-start=\"1672\" data-end=\"1692\"\u003eCatégorie de produit\u003c\/strong\u003e : Bibliothèque \/ Framework de Machine Learning\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1736\" data-end=\"1780\"\u003e\n\n\u003cp data-start=\"1738\" data-end=\"1780\"\u003e\u003cstrong data-start=\"1738\" data-end=\"1752\"\u003eType de produit\u003c\/strong\u003e : Module Python open source\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1781\" data-end=\"1908\"\u003e\n\n\u003cp data-start=\"1783\" data-end=\"1908\"\u003e\u003cstrong data-start=\"1783\" data-end=\"1795\"\u003eFournisseur\u003c\/strong\u003e : Communauté \/ Projet open source (notamment contributions de Google, INRIA, etc.) \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/en.wikipedia.org\/wiki\/Scikit-learn?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/en.wikipedia.org\/wiki\/Scikit-learn?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eScikit-learn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+3\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eWikipedia\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+3\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eGitHub\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+3\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1909\" data-end=\"2120\"\u003e\n\n\u003cp data-start=\"1911\" data-end=\"2120\"\u003e\u003cstrong data-start=\"1911\" data-end=\"1941\"\u003eComposants \/ Éléments\u003c\/strong\u003e :\u003cbr data-start=\"1942\" data-end=\"1945\"\u003e • Classifieurs \u0026amp; Régressions\u003cbr data-start=\"1977\" data-end=\"1980\"\u003e • Algorithmes de clustering\u003cbr data-start=\"2002\" data-end=\"2005\"\u003e • Pipeline \/ Prétraitement\u003cbr data-start=\"2032\" data-end=\"2035\"\u003e • Sélection de modèle \u0026amp; réglage d'hyperparamètres\u003cbr data-start=\"2077\" data-end=\"2080\"\u003e • Outils de réduction de dimensionnalité\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2121\" data-end=\"2230\"\u003e\n\n\u003cp data-start=\"2123\" data-end=\"2230\"\u003e\u003cstrong data-start=\"2123\" data-end=\"2141\"\u003eTags pertinents\u003c\/strong\u003e : #MachineLearning 🤖 #Python 🐍 #OpenSource 🌱 #scikit-learn #DataScience #Algorithmes\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003chr data-start=\"2232\" data-end=\"2235\"\u003e\n\u003ch2 data-start=\"2237\" data-end=\"2264\"\u003e🧰 Exemples d'application\u003c\/h2\u003e\n\u003cul data-start=\"2266\" data-end=\"2514\"\u003e\n\n\u003cli data-start=\"2266\" data-end=\"2309\"\u003e\n\n\u003cp data-start=\"2268\" data-end=\"2309\"\u003eClassification d'images ou de textes\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2310\" data-end=\"2348\"\u003e\n\n\u003cp data-start=\"2312\" data-end=\"2348\"\u003ePrévisions (par ex. prédiction de prix)\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2349\" data-end=\"2379\"\u003e\n\n\u003cp data-start=\"2351\" data-end=\"2379\"\u003eClustering de données clients\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2380\" data-end=\"2425\"\u003e\n\n\u003cp data-start=\"2382\" data-end=\"2425\"\u003ePrétraitement des données, Feature Engineering\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2426\" data-end=\"2466\"\u003e\n\n\u003cp data-start=\"2428\" data-end=\"2466\"\u003eComparaison de modèles avec validation croisée\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2467\" data-end=\"2514\"\u003e\n\n\u003cp data-start=\"2469\" data-end=\"2514\"\u003eUtilisation en recherche, prototypage et enseignement\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e","brand":"Antus","offers":[{"title":"Default Title","offer_id":53595750269260,"sku":null,"price":1.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0933\/9011\/1052\/files\/Scikit-learn_Die_bew_hrte_Machine_Learning_Bibliothek_f_r_Python.png?v=1760390268"},{"product_id":"pytorch-flexibles-deep-learning-framework-fur-forschung","title":"PyTorch – Framework de deep learning flexible pour la recherche 🪴","description":"\u003ch3 data-start=\"285\" data-end=\"310\"\u003e🧠 Qu'est-ce que PyTorch ?\u003c\/h3\u003e\n\u003cp data-start=\"312\" data-end=\"716\"\u003e\u003cstrong data-start=\"312\" data-end=\"323\"\u003ePyTorch\u003c\/strong\u003e est un framework open source puissant dédié au \u003cstrong data-start=\"372\" data-end=\"389\"\u003eDeep Learning\u003c\/strong\u003e. Développé par \u003cstrong data-start=\"406\" data-end=\"417\"\u003eMeta AI\u003c\/strong\u003e, il permet aux chercheurs et aux développeurs de concevoir, d'entraîner et de déployer rapidement des réseaux de neurones dans des applications réelles. PyTorch allie facilité d'utilisation et haute performance, offrant tout ce dont les projets d'IA modernes ont besoin – de l'expérimentation au déploiement en production.\u003c\/p\u003e\n\u003chr data-start=\"718\" data-end=\"721\"\u003e\n\u003ch3 data-start=\"723\" data-end=\"759\"\u003e🌟 Avantages et particularités\u003c\/h3\u003e\n\u003cul data-start=\"761\" data-end=\"1481\"\u003e\n\n\u003cli data-start=\"761\" data-end=\"920\"\u003e\n\n\u003cp data-start=\"763\" data-end=\"920\"\u003e\u003cstrong data-start=\"763\" data-end=\"788\"\u003eCalcul dynamique\u003c\/strong\u003e – PyTorch utilise un principe « define-by-run » qui permet aux développeurs d'adapter les modèles de manière flexible et de les déboguer intuitivement 🧩\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"921\" data-end=\"1047\"\u003e\n\n\u003cp data-start=\"923\" data-end=\"1047\"\u003e\u003cstrong data-start=\"923\" data-end=\"955\"\u003eDifférenciation automatique\u003c\/strong\u003e – Grâce à « Autograd », les gradients peuvent être calculés efficacement, ce qui est idéal pour les réseaux de neurones 🤖\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1048\" data-end=\"1170\"\u003e\n\n\u003cp data-start=\"1050\" data-end=\"1170\"\u003e\u003cstrong data-start=\"1050\" data-end=\"1081\"\u003eIntégration Python fluide\u003c\/strong\u003e – PyTorch est facile à apprendre et s'intègre parfaitement dans l'écosystème Python 🐍\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1171\" data-end=\"1291\"\u003e\n\n\u003cp data-start=\"1173\" data-end=\"1205\"\u003ePrise en charge des \u003cstrong data-start=\"1173\" data-end=\"1205\"\u003eGPU et du Cloud\u003c\/strong\u003e – Entraînement sur des supercalculateurs, des systèmes distribués et des infrastructures Cloud ⚡\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1292\" data-end=\"1391\"\u003e\n\n\u003cp data-start=\"1294\" data-end=\"1391\"\u003e\u003cstrong data-start=\"1294\" data-end=\"1314\"\u003eVaste écosystème\u003c\/strong\u003e – Avec des extensions pour la vision par ordinateur, le traitement automatique du langage naturel (NLP) et l'apprentissage par renforcement 📚\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1392\" data-end=\"1481\"\u003e\n\n\u003cp data-start=\"1394\" data-end=\"1481\"\u003e\u003cstrong data-start=\"1394\" data-end=\"1409\"\u003eOpen Source\u003c\/strong\u003e – Utilisé dans le monde entier et constamment amélioré par une communauté active 🌍\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003chr data-start=\"1483\" data-end=\"1486\"\u003e\n\u003ch3 data-start=\"1488\" data-end=\"1513\"\u003e🧭 Vision et valeurs\u003c\/h3\u003e\n\u003cp data-start=\"1515\" data-end=\"1841\"\u003ePyTorch a pour objectif de rendre la \u003cstrong data-start=\"1542\" data-end=\"1643\"\u003erecherche et le développement dans le domaine de l'intelligence artificielle accessibles, transparents et innovants\u003c\/strong\u003e. Le framework prône la flexibilité, la rapidité et la collaboration ouverte. Il est utilisé par des instituts de recherche de premier plan, des start-ups et des entreprises technologiques mondiales.\u003c\/p\u003e\n\u003chr data-start=\"1843\" data-end=\"1846\"\u003e\n\u003ch3 data-start=\"1848\" data-end=\"1878\"\u003e🧰 Possibilités d'utilisation\u003c\/h3\u003e\n\u003cp data-start=\"1880\" data-end=\"1935\"\u003e\u003cstrong data-start=\"1880\" data-end=\"1891\"\u003ePyTorch\u003c\/strong\u003e est appliqué dans de nombreux domaines :\u003c\/p\u003e\n\u003cul data-start=\"1936\" data-end=\"2329\"\u003e\n\n\u003cli data-start=\"1936\" data-end=\"2019\"\u003e\n\n\u003cp data-start=\"1938\" data-end=\"2019\"\u003ePour la \u003cstrong data-start=\"1942\" data-end=\"1959\"\u003ereconnaissance d'images\u003c\/strong\u003e, la \u003cstrong data-start=\"1961\" data-end=\"1980\"\u003edétection d'objets\u003c\/strong\u003e et l' \u003cstrong data-start=\"1985\" data-end=\"2013\"\u003eanalyse d'imagerie médicale\u003c\/strong\u003e 🖼️\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2020\" data-end=\"2098\"\u003e\n\n\u003cp data-start=\"2022\" data-end=\"2098\"\u003eDans le \u003cstrong data-start=\"2029\" data-end=\"2051\"\u003etraitement du langage\u003c\/strong\u003e pour la traduction, les chatbots et l'analyse de texte 💬\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2099\" data-end=\"2175\"\u003e\n\n\u003cp data-start=\"2101\" data-end=\"2175\"\u003ePour les \u003cstrong data-start=\"2105\" data-end=\"2129\"\u003emodèles génératifs\u003c\/strong\u003e tels que l'art IA, la génération de texte et de musique 🎨\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2176\" data-end=\"2250\"\u003e\n\n\u003cp data-start=\"2178\" data-end=\"2250\"\u003eDans la \u003cstrong data-start=\"2185\" data-end=\"2198\"\u003erecherche\u003c\/strong\u003e pour développer de nouvelles architectures neuronales 🔬\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2251\" data-end=\"2329\"\u003e\n\n\u003cp data-start=\"2253\" data-end=\"2329\"\u003ePour les \u003cstrong data-start=\"2257\" data-end=\"2279\"\u003esystèmes de production\u003c\/strong\u003e dans des environnements Cloud ou sur des appareils mobiles 📱\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e","brand":"Antus","offers":[{"title":"Default Title","offer_id":53599577637196,"sku":null,"price":1.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0933\/9011\/1052\/files\/PyTorch_Flexibles_Deep_Learning_Framework_f_r_Forschung.png?v=1760437083"},{"product_id":"onnx-format-fur-ki-modelle-zur-interoperabilitat-zwischen-frameworks-🛠️","title":"ONNX – Format de modèles d'IA pour l'interopérabilité entre frameworks 🪴🛠️","description":"\u003ch3 data-start=\"197\" data-end=\"217\"\u003e🧠 Qu'est-ce qu'ONNX ?\u003c\/h3\u003e\n\u003cp data-start=\"219\" data-end=\"599\"\u003eONNX (Open Neural Network Exchange) est un format ouvert, développé pour permettre aux équipes de développement d'entraîner des modèles dans un framework et de les déployer dans un autre, sans avoir à les réécrire. L'objectif est de réduire les frictions entre les différents outils d'IA et d'accélérer le passage de la recherche à la production. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/onnx.ai\/about.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/onnx.ai\/about.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eonnx.ai\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eonnx.ai\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003chr data-start=\"601\" data-end=\"604\"\u003e\n\u003ch3 data-start=\"606\" data-end=\"640\"\u003e🌟 Avantages et particularités\u003c\/h3\u003e\n\u003cul data-start=\"642\" data-end=\"1334\"\u003e\n\n\u003cli data-start=\"642\" data-end=\"795\"\u003e\n\n\u003cp data-start=\"644\" data-end=\"795\"\u003e\u003cstrong data-start=\"644\" data-end=\"672\"\u003eIndépendance vis-à-vis des frameworks\u003c\/strong\u003e : Phase d'entraînement possible dans, par exemple, PyTorch, et déploiement dans TensorFlow ou ONNX Runtime. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/docs.oracle.com\/en\/database\/oracle\/machine-learning\/oml4sql\/23\/dmprg\/onnx.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/docs.oracle.com\/en\/database\/oracle\/machine-learning\/oml4sql\/23\/dmprg\/onnx.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eOracle Docs\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eonnx.ai\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"796\" data-end=\"984\"\u003e\n\n\u003cp data-start=\"798\" data-end=\"984\"\u003e\u003cstrong data-start=\"798\" data-end=\"822\"\u003eOptimisation des performances\u003c\/strong\u003e : ONNX Runtime propose des optimisations pour divers environnements matériels tels que les processeurs (CPU), les cartes graphiques (GPU) ou des accélérateurs spécialisés. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/vraspar.github.io\/onnxruntime\/about.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/vraspar.github.io\/onnxruntime\/about.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003evraspar.github.io\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eonnx.ai\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"985\" data-end=\"1164\"\u003e\n\n\u003cp data-start=\"987\" data-end=\"1164\"\u003e\u003cstrong data-start=\"987\" data-end=\"1020\"\u003eStructure de graphe standardisée\u003c\/strong\u003e : Les modèles sont enregistrés sous forme de graphe de calcul acyclique avec des opérateurs et des types de données définis. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/onnx.ai\/about.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/onnx.ai\/about.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eonnx.ai\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eonnx.ai\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1165\" data-end=\"1334\"\u003e\n\n\u003cp data-start=\"1167\" data-end=\"1334\"\u003e\u003cstrong data-start=\"1167\" data-end=\"1187\"\u003eÉcosystème étendu\u003c\/strong\u003e : De nombreux frameworks prennent en charge l'exportation vers ONNX ; des outils de visualisation et d'optimisation sont disponibles. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/github.com\/onnx\/onnx?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/github.com\/onnx\/onnx?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eGitHub\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eonnx.ai\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003chr data-start=\"1336\" data-end=\"1339\"\u003e\n\u003ch3 data-start=\"1341\" data-end=\"1364\"\u003e🧭 Vision et valeurs\u003c\/h3\u003e\n\u003cp data-start=\"1366\" data-end=\"1633\"\u003eONNX aspire à offrir une liberté aux développeurs, à encourager l'innovation et à éviter que les équipes ne soient limitées par une dépendance à un framework spécifique. L'objectif est un monde de l'IA où les modèles et les outils peuvent collaborer sans barrières artificielles. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/onnx.ai\/about.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/onnx.ai\/about.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between overflow-hidden\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eonnx.ai\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003chr data-start=\"1635\" data-end=\"1638\"\u003e\n\u003ch3 data-start=\"1640\" data-end=\"1668\"\u003e🧰 Possibilités d'utilisation\u003c\/h3\u003e\n\u003cul data-start=\"1670\" data-end=\"2107\"\u003e\n\n\u003cli data-start=\"1670\" data-end=\"1806\"\u003e\n\n\u003cp data-start=\"1672\" data-end=\"1806\"\u003eÉchange de modèles entre différents frameworks d'IA, par exemple, phase d'entraînement dans un outil et déploiement dans un autre\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1807\" data-end=\"1882\"\u003e\n\n\u003cp data-start=\"1809\" data-end=\"1882\"\u003eUtilisation dans des environnements de production à faible latence grâce à ONNX Runtime\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1883\" data-end=\"1959\"\u003e\n\n\u003cp data-start=\"1885\" data-end=\"1959\"\u003eUtilisation dans des environnements accélérés par le matériel (par ex. GPU, appareils Edge)\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1960\" data-end=\"2018\"\u003e\n\n\u003cp data-start=\"1962\" data-end=\"2018\"\u003eVisualisation, débogage et optimisation de modèles\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"2019\" data-end=\"2107\"\u003e\n\n\u003cp data-start=\"2021\" data-end=\"2107\"\u003eRecherche et prototypage, par exemple pour le développement de nouvelles architectures ou une itération rapide\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e","brand":"Antus","offers":[{"title":"Default Title","offer_id":53599620825420,"sku":null,"price":1.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0933\/9011\/1052\/files\/Screenshot2025-10-14122015.png?v=1760437243"},{"product_id":"mindspore-intelligentes-deep-learning-framework-fur-cloud-edge-und-gerate","title":"MindSpore – Cadre de deep learning intelligent pour le cloud, l'edge et les appareils 🪴","description":"\u003ch3 data-start=\"189\" data-end=\"214\"\u003e🧠 Qu'est-ce que MindSpore ?\u003c\/h3\u003e\n\u003cp data-start=\"216\" data-end=\"507\"\u003e\u003cstrong data-start=\"216\" data-end=\"229\"\u003eMindSpore\u003c\/strong\u003e est un framework de Deep Learning open-source développé par Huawei, utilisable dans tous les scénarios – du cloud à la périphérie (edge) jusqu'aux appareils mobiles. Il allie développement simplifié, exécution efficace et déploiement flexible. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.mindspore.cn\/tutorials\/en\/r1.7\/beginner\/introduction.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.mindspore.cn\/tutorials\/en\/r1.7\/beginner\/introduction.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003emindspore.cn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003eGitHub\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003chr data-start=\"509\" data-end=\"512\"\u003e\n\u003ch3 data-start=\"514\" data-end=\"548\"\u003e🌟 Avantages et particularités\u003c\/h3\u003e\n\u003cul data-start=\"550\" data-end=\"1318\"\u003e\n\n\u003cli data-start=\"550\" data-end=\"701\"\u003e\n\n\u003cp data-start=\"552\" data-end=\"701\"\u003e\u003cstrong data-start=\"552\" data-end=\"591\"\u003eAPI simple et débogage intuitif\u003c\/strong\u003e – Les développeurs peuvent se concentrer sur les modèles plutôt que sur le code standard (boilerplate). \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.mindspore.cn\/tutorials\/en\/r1.7\/beginner\/introduction.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.mindspore.cn\/tutorials\/en\/r1.7\/beginner\/introduction.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003emindspore.cn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"702\" data-end=\"875\"\u003e\n\n\u003cp data-start=\"704\" data-end=\"875\"\u003e\u003cstrong data-start=\"704\" data-end=\"729\"\u003eExécution efficace\u003c\/strong\u003e – Les optimisations sont effectuées avant l'exécution, comme les optimisations de compilateur et la co-optimisation matérielle. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/mindspore-website.obs.cn-north-4.myhuaweicloud.com\/white_paper\/MindSpore_white_paper_enV1.1.pdf?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/mindspore-website.obs.cn-north-4.myhuaweicloud.com\/white_paper\/MindSpore_white_paper_enV1.1.pdf?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003emindspore-website.obs.cn-north-4.myhuaweicloud.com\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"876\" data-end=\"1020\"\u003e\n\n\u003cp data-start=\"878\" data-end=\"1020\"\u003e\u003cstrong data-start=\"878\" data-end=\"909\"\u003ePrise en charge tous scénarios\u003c\/strong\u003e – Utilisation possible sur des appareils, des systèmes edge ou dans des environnements cloud. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.mindspore.cn\/tutorials\/en\/r1.7\/beginner\/introduction.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.mindspore.cn\/tutorials\/en\/r1.7\/beginner\/introduction.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003emindspore.cn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003emindspore.cn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1021\" data-end=\"1183\"\u003e\n\n\u003cp data-start=\"1023\" data-end=\"1183\"\u003e\u003cstrong data-start=\"1023\" data-end=\"1056\"\u003eOptimisé pour le matériel Huawei\u003c\/strong\u003e – Prise en charge des processeurs Ascend ; co-optimisation entre logiciel et matériel. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.mindspore.cn\/tutorials\/en\/r1.6\/introduction.html?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.mindspore.cn\/tutorials\/en\/r1.6\/introduction.html?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003emindspore.cn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between absolute\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003emindspore-website.obs.cn-north-4.myhuaweicloud.com\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+2\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1184\" data-end=\"1318\"\u003e\n\n\u003cp data-start=\"1186\" data-end=\"1318\"\u003e\u003cstrong data-start=\"1186\" data-end=\"1223\"\u003eOpen Source avec une communauté active\u003c\/strong\u003e – Contributions, modèles et extensions disponibles librement. \u003cspan class=\"\" data-state=\"closed\"\u003e\u003cspan class=\"ms-1 inline-flex max-w-full items-center relative top-[-0.094rem] animate-[show_150ms_ease-in]\" data-testid=\"webpage-citation-pill\"\u003e\u003ca href=\"https:\/\/www.mindspore.cn\/en\/?utm_source=chatgpt.com\" rel=\"noopener\" alt=\"https:\/\/www.mindspore.cn\/en\/?utm_source=chatgpt.com\" class=\"flex h-4.5 overflow-hidden rounded-xl px-2 text-[9px] font-medium transition-colors duration-150 ease-in-out text-token-text-secondary! bg-[#F4F4F4]! dark:bg-[#303030]!\" target=\"_blank\"\u003e\u003cspan class=\"relative start-0 bottom-0 flex h-full w-full items-center\"\u003e\u003cspan class=\"flex h-4 w-full items-center justify-between\"\u003e\u003cspan class=\"max-w-[15ch] grow truncate overflow-hidden text-center\"\u003emindspore.cn\u003c\/span\u003e\u003cspan class=\"-me-1 flex h-full items-center rounded-full px-1 text-[#8F8F8F]\"\u003e+1\u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003chr data-start=\"1320\" data-end=\"1323\"\u003e\n\u003ch3 data-start=\"1325\" data-end=\"1353\"\u003e🧰 Possibilités d'utilisation\u003c\/h3\u003e\n\u003cul data-start=\"1355\" data-end=\"1679\"\u003e\n\n\u003cli data-start=\"1355\" data-end=\"1436\"\u003e\n\n\u003cp data-start=\"1357\" data-end=\"1436\"\u003e\u003cstrong data-start=\"1357\" data-end=\"1389\"\u003eTraitement d'images et d'objets\u003c\/strong\u003e – Classification, segmentation, IA visuelle\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1437\" data-end=\"1510\"\u003e\n\n\u003cp data-start=\"1439\" data-end=\"1510\"\u003e\u003cstrong data-start=\"1439\" data-end=\"1471\"\u003eTraitement du langage et du texte\u003c\/strong\u003e – PNL, analyse de sentiment, traduction\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1511\" data-end=\"1557\"\u003e\n\n\u003cp data-start=\"1513\" data-end=\"1557\"\u003e\u003cstrong data-start=\"1513\" data-end=\"1555\"\u003eDéploiement de modèles sur Edge ou appareils\u003c\/strong\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1558\" data-end=\"1631\"\u003e\n\n\u003cp data-start=\"1560\" data-end=\"1631\"\u003e\u003cstrong data-start=\"1560\" data-end=\"1587\"\u003eRecherche et prototypage\u003c\/strong\u003e – Expérimentation avec de nouvelles architectures\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli data-start=\"1632\" data-end=\"1679\"\u003e\n\n\u003cp data-start=\"1634\" data-end=\"1679\"\u003e\u003cstrong data-start=\"1634\" data-end=\"1677\"\u003eUtilisation de l'IA dans des applications industrielles\u003c\/strong\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e","brand":"Antus","offers":[{"title":"Default Title","offer_id":53599684624716,"sku":null,"price":1.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0933\/9011\/1052\/files\/MindSpore_Intelligentes_Deep_Learning_Framework_f_r_Cloud_Edge_und_Ger_te.png?v=1760437921"}],"url":"https:\/\/antus.de\/fr\/collections\/multiframework-ki-systeme.oembed","provider":"Antus","version":"1.0","type":"link"}