{"id":6217,"date":"2019-11-06T15:38:47","date_gmt":"2019-11-06T15:38:47","guid":{"rendered":"https:\/\/www.kolabtree.com\/blog\/?p=6217"},"modified":"2020-11-09T05:58:32","modified_gmt":"2020-11-09T05:58:32","slug":"top-machine-learning-applications-in-mobile-apps","status":"publish","type":"post","link":"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/","title":{"rendered":"Principales applications d'apprentissage automatique dans les applications mobiles"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_45_1 counter-flat ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\">Table des mati\u00e8res<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" area-label=\"ez-toc-toggle-icon-1\"><label for=\"item-69f19e127aab7\" aria-label=\"Table des mati\u00e8res\"><span style=\"display: flex;align-items: center;width: 35px;height: 30px;justify-content: center;direction:ltr;\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/label><input  type=\"checkbox\" id=\"item-69f19e127aab7\"><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/#Finance_and_Banking\" title=\"Finance et banque\">Finance et banque<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/#Healthcare\" title=\"Soins de sant\u00e9\u00a0\">Soins de sant\u00e9\u00a0<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/#Retail_and_ecommerce\" title=\"Commerce de d\u00e9tail et commerce \u00e9lectronique\u00a0\">Commerce de d\u00e9tail et commerce \u00e9lectronique\u00a0<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/#Advertising_Marketing\" title=\"Publicit\u00e9 et marketing\">Publicit\u00e9 et marketing<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/#Real-World_Applications_of_Machine_Learning_in_Mobile_Apps\" title=\"Applications r\u00e9elles de l&#039;apprentissage automatique dans les applications mobiles\u00a0\">Applications r\u00e9elles de l'apprentissage automatique dans les applications mobiles\u00a0<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/#Netflix\" title=\"Netflix\">Netflix<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/#Tinder\" title=\"Tinder\">Tinder<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/#Snapchat\" title=\"Snapchat\">Snapchat<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/#Google_Maps\" title=\"Google Maps\">Google Maps<\/a><\/li><\/ul><\/nav><\/div>\n<p><span style=\"font-weight: 400;\"><em>Juned Ghanchi \u00e9crit \u00e0 propos du sommet <a href=\"https:\/\/www.kolabtree.com\/find-an-expert\/subject\/machine-learning?utm_source=Blog&amp;utm_medium=Post&amp;utm_campaign=MLMobileApps\">apprentissage machine<\/a> dans des applications mobiles, dont certaines sont utilis\u00e9es quotidiennement par nombre d'entre nous. <\/em><\/span><\/p>\n<p><span style=\"font-weight: 400;\">Mobile apps, thanks to their all-pervading and all-encompassing role across all spheres of life, have been the subject of several state-of-the-art technologies and innovations. For mobile apps to stand out from the crowd, new technologies are playing an instrumental role. As the demand for personalised user experience is exponentially growing across all digital applications, new technologies like Machine Learning and <a href=\"https:\/\/www.kolabtree.com\/blog\/fr\/ensuring-reproducibility-in-ai-driven-research-how-freelance-experts-can-help-in-biotech-and-healthcare\/\">Intelligence artificielle<\/a> are playing a decisive role in meeting this demand.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Mais comment l'apprentissage automatique peut-il renforcer les applications mobiles ? L'apprentissage automatique est utilis\u00e9 par les d\u00e9veloppeurs d'applications mobiles pour fournir des fonctionnalit\u00e9s am\u00e9lior\u00e9es, allant de la reconnaissance des visages et de la d\u00e9tection des personnes aux moteurs de recommandation personnalis\u00e9s. Voici quelques applications int\u00e9ressantes de l'apprentissage automatique dans les applications mobiles.\u00a0<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Finance_and_Banking\"><\/span><b>Finance et banque<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">L'analyse pr\u00e9dictive dans le secteur de la finance et de la banque est d'une importance capitale car la pr\u00e9vision pr\u00e9cise des crises, des bulles \u00e9conomiques ou des tendances peut aider les organisations \u00e0 se tenir \u00e0 l'\u00e9cart des facteurs de risque tout en optimisant les opportunit\u00e9s de croissance. <\/span><b>Cr\u00e9ation d'une assurance <a href=\"https:\/\/econsultancy.com\/how-lemonade-disrupted-the-insurance-industry-and-built-a-multi-billion-dollar-business\/\">Limonade<\/a> a lanc\u00e9 une application pour smartphone, qui utilise le ML et les chatbots pour fournir des services d'assurance.\u00a0<\/b><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Healthcare\"><\/span><b>Soins de sant\u00e9\u00a0<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Les soins de sant\u00e9 sont un autre secteur crucial o\u00f9 l'apprentissage automatique devrait jouer un r\u00f4le important. Qu'il s'agisse de diagnostics de pr\u00e9cision bas\u00e9s sur le comportement de l'utilisateur ou de soins de sant\u00e9 plus proactifs et r\u00e9actifs bas\u00e9s sur les donn\u00e9es du patient, cette technologie peut apporter beaucoup d'efficacit\u00e9 et de fiabilit\u00e9 aux pratiques de soins de sant\u00e9 modernes. Pour certaines maladies potentiellement mortelles, comme le cancer, qui n\u00e9cessitent une d\u00e9tection et un diagnostic pr\u00e9coces, l'apprentissage proactif des sympt\u00f4mes du patient peut vraiment jouer un r\u00f4le essentiel. L'apprentissage automatique peut \u00e9galement ouvrir la voie \u00e0 des m\u00e9dicaments et des traitements plus personnalis\u00e9s pour des affections de nature diff\u00e9rente. <\/span><a href=\"https:\/\/www.kolabtree.com\/blog\/wearable-technology-changing-the-face-of-healthcare\/\"><b>Wearables<\/b><\/a><b> et les applications mobiles qui leur sont associ\u00e9es jouent actuellement un r\u00f4le \u00e9norme, en aidant \u00e0 surveiller la sant\u00e9 en temps r\u00e9el et \u00e0 fournir des informations en retour.\u00a0<\/b><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Retail_and_ecommerce\"><\/span><b>Commerce de d\u00e9tail et commerce \u00e9lectronique\u00a0<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Dans l'ensemble du secteur du commerce de d\u00e9tail, y compris les magasins de commerce \u00e9lectronique, la connaissance du comportement et des habitudes des clients joue un r\u00f4le crucial. Conna\u00eetre les pr\u00e9f\u00e9rences, les penchants et les intentions des clients peut aider les magasins \u00e0 r\u00e9pondre aux besoins et aux choix des clients de mani\u00e8re plus pr\u00e9cise et plus pertinente. Des recommandations personnalis\u00e9es bas\u00e9es sur les entr\u00e9es des utilisateurs peuvent aider un magasin \u00e0 saisir les opportunit\u00e9s de vente de mani\u00e8re plus pr\u00e9cise. Certains des domaines cl\u00e9s o\u00f9 le commerce \u00e9lectronique <\/span><a href=\"https:\/\/www.indianappdevelopers.com\/\"><span style=\"font-weight: 400;\">d\u00e9veloppeurs d'applications<\/span><\/a><span style=\"font-weight: 400;\"> La recherche de produits, les recommandations, la pr\u00e9vision des tendances, les promotions et les m\u00e9canismes de contr\u00f4le des fraudes sont autant de domaines dans lesquels les informations bas\u00e9es sur le ML peuvent vraiment \u00eatre utiles. <\/span><b>Le g\u00e9ant du commerce \u00e9lectronique Amazon est un exemple d'application mobile d'achat utilisant le ML.\u00a0<\/b><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Advertising_Marketing\"><\/span>Publicit\u00e9 et marketing<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Plusieurs marques exploitent la puissance du ML pour pr\u00e9senter des publicit\u00e9s pertinentes aux utilisateurs cibl\u00e9s. <a href=\"https:\/\/digiday.com\/marketing\/coca-cola-targeted-ads-based-facebook-instagram-photos\/\">Coca cola,<\/a> par exemple, utilise un algorithme de reconnaissance d'image pour d\u00e9tecter automatiquement les images de ses produits lorsque les utilisateurs t\u00e9l\u00e9chargent des photos sur les m\u00e9dias sociaux. Sur la base de ces informations, elle exploite ensuite la conversation et g\u00e9n\u00e8re des publicit\u00e9s \u00e0 destination de publics pertinents. Certaines entreprises utilisent \u00e9galement la g\u00e9olocalisation pour vous montrer des notifications mobiles lorsque vous vous rapprochez d'un magasin sur lequel vous avez d\u00e9j\u00e0 consult\u00e9 des produits.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\"><cite>Lire la suite de Kolabtree : <a href=\"https:\/\/www.kolabtree.com\/blog\/5-companies-using-big-data-and-ai-to-improve-performance\/\">5 entreprises utilisant le Big Data et l'IA pour am\u00e9liorer leurs performances<\/a><\/cite><br \/>\n<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Real-World_Applications_of_Machine_Learning_in_Mobile_Apps\"><\/span><b>Applications r\u00e9elles de l'apprentissage automatique dans les applications mobiles\u00a0<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"Netflix\"><\/span><b>Netflix<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Netflix, l'application de streaming vid\u00e9o et multim\u00e9dia, utilise l'apprentissage automatique pour am\u00e9liorer l'exp\u00e9rience et l'engagement des utilisateurs. Netflix utilise l'apprentissage automatique pour r\u00e9pondre aux pr\u00e9f\u00e9rences, aux choix et aux intentions de l'utilisateur, en fonction de ses activit\u00e9s. <\/span><a href=\"https:\/\/research.netflix.com\/research-area\/machine-learning\"><span style=\"font-weight: 400;\">Recherche sur Netflix<\/span><\/a><span style=\"font-weight: 400;\"> d\u00e9crit comment le ML est utilis\u00e9 efficacement \u00e0 travers leur r\u00e9seau.\u00a0\u00a0<\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Tinder\"><\/span><b>Tinder<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Tinder, l'application de rencontre mondialement populaire, a d\u00e9j\u00e0 battu tous les records en termes d'engagement et de satisfaction des utilisateurs parmi toutes les autres applications de rencontre. Tinder utilise d\u00e9sormais un algorithme d'apprentissage automatique pour comprendre plus pr\u00e9cis\u00e9ment l'intention et les pr\u00e9f\u00e9rences des utilisateurs et d\u00e9terminer comment leur montrer un profil sur lequel ils sont susceptibles de glisser vers la droite. Vox explique l'algorithme de Tinder <\/span><a href=\"https:\/\/www.vox.com\/2019\/2\/7\/18210998\/tinder-algorithm-swiping-tips-dating-app-science\"><span style=\"font-weight: 400;\">ici<\/span><\/a><span style=\"font-weight: 400;\">.\u00a0<\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Snapchat\"><\/span><b>Snapchat<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">L'apprentissage automatique ne consiste pas seulement \u00e0 offrir aux clients des recommandations parfaites pour assurer un rendement constant des ventes. Snapchat est l'une des rares applications \u00e0 succ\u00e8s \u00e0 avoir exploit\u00e9 toutes les capacit\u00e9s de la technologie d'apprentissage automatique. Des filtres comme 3D Paint dans Snapchat sont de bons exemples de la mani\u00e8re dont la r\u00e9alit\u00e9 augment\u00e9e et l'apprentissage automatique peuvent \u00eatre utilis\u00e9s conjointement pour am\u00e9liorer la vision par ordinateur.\u00a0<\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Google_Maps\"><\/span><b>Google Maps<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\"><img decoding=\"async\" loading=\"lazy\" class=\"alignnone size-medium wp-image-6223\" src=\"https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2019\/11\/machine-learning-applications-mobile-apps-300x200.jpg\" alt=\"\" width=\"300\" height=\"200\" srcset=\"https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2019\/11\/machine-learning-applications-mobile-apps-300x200.jpg 300w, https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2019\/11\/machine-learning-applications-mobile-apps-1024x683.jpg 1024w, https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2019\/11\/machine-learning-applications-mobile-apps-768x512.jpg 768w, https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2019\/11\/machine-learning-applications-mobile-apps-1080x720.jpg 1080w, https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2019\/11\/machine-learning-applications-mobile-apps.jpg 1350w, https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2019\/11\/machine-learning-applications-mobile-apps-300x200@2x.jpg 600w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><br \/>\nL'utilisation de l'apprentissage automatique par Google Maps est un autre exemple frappant de la mani\u00e8re dont cette technologie peut garantir une efficacit\u00e9 et une convivialit\u00e9 optimales pour les utilisateurs finaux. Au lieu d'attendre \u00e0 chaque fois l'entr\u00e9e et la commande d'un utilisateur, Google Maps utilise le ML pour pr\u00e9dire <\/span><a href=\"https:\/\/venturebeat.com\/2019\/06\/27\/how-google-maps-uses-machine-learning-to-predict-bus-traffic-delays-in-real-time\/\"><span style=\"font-weight: 400;\">retards de bus<\/span><\/a><span style=\"font-weight: 400;\">, <\/span><a href=\"https:\/\/ai.googleblog.com\/2017\/05\/updating-google-maps-with-deep-learning.html\"><span style=\"font-weight: 400;\">lire les noms des rues<\/span><\/a><span style=\"font-weight: 400;\">et plus encore.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">En conclusion, le ML et l'IA ouvrent la voie \u00e0 des applications plus intelligentes et conviviales pour les clients, ce qui \u00e9tait impensable il y a seulement quelques ann\u00e9es. L'avenir des applications mobiles et des interactions num\u00e9riques appartient \u00e0 ces technologies intelligentes.<\/span><\/p>\n<p><strong>Vous souhaitez parler \u00e0 un <a href=\"https:\/\/www.kolabtree.com\/find-an-expert\/subject\/machine-learning?utm_source=Blog&amp;utm_medium=Post&amp;utm_campaign=MLMobileApps\">consultant en apprentissage machine<\/a>? Travaillez avec des experts en ML, IA et science des donn\u00e9es sur Kolabtree.\u00a0<\/strong><\/p>","protected":false},"excerpt":{"rendered":"<p>Juned Ghanchi pr\u00e9sente les principales applications d'apprentissage automatique dans les applications mobiles, dont certaines sont utilis\u00e9es quotidiennement par beaucoup d'entre nous. Les applications mobiles, gr\u00e2ce \u00e0 leur r\u00f4le omnipr\u00e9sent dans tous les domaines de la vie, ont fait l'objet de plusieurs technologies et innovations de pointe. Pour que les applications mobiles se distinguent des autres<\/p>\n<div class=\"read-more\"><a href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/\" title=\"Lire la suite\">Lire la suite<\/a><\/div>","protected":false},"author":12,"featured_media":6221,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[434,398,247,433],"tags":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.1 (Yoast SEO v20.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Top Machine Learning Applications in Mobile Apps - The Kolabtree Blog<\/title>\n<meta name=\"description\" content=\"Machine learning applications in mobile apps range from face recognition to personalized recommendations. Here are some interesting use cases.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Top Machine Learning Applications in Mobile Apps\" \/>\n<meta property=\"og:description\" content=\"Machine learning applications in mobile apps range from face recognition to personalized recommendations. Here are some interesting use cases.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.kolabtree.com\/blog\/fr\/top-machine-learning-applications-in-mobile-apps\/\" \/>\n<meta property=\"og:site_name\" content=\"The Kolabtree Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/kolabtree\" \/>\n<meta property=\"article:published_time\" content=\"2019-11-06T15:38:47+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2020-11-09T05:58:32+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2019\/11\/machine-learning-mobile-apps.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1350\" \/>\n\t<meta property=\"og:image:height\" content=\"900\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Ramya Sriram\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@kolabtree\" \/>\n<meta name=\"twitter:site\" content=\"@kolabtree\" \/>\n<meta name=\"twitter:label1\" content=\"\u00c9crit par\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ramya Sriram\" \/>\n\t<meta name=\"twitter:label2\" content=\"Dur\u00e9e de lecture estim\u00e9e\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Top Machine Learning Applications in Mobile Apps - The Kolabtree Blog","description":"Machine learning applications in mobile apps range from face recognition to personalized recommendations. 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