--- description: TensorFlow : avantages et inconvénients. Lisez les avis clients, consultez les prix et découvrez les fonctionnalités. image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: TensorFlow - Avis, notes, prix et abonnements - Capterra Canada 2026 --- Breadcrumb: [Accueil](/) > [Outils d'apprentissage automatique](/directory/31103/machine-learning/software) > [TensorFlow](/software/171057/tensorflow) # TensorFlow Canonical: https://fr.capterra.ca/software/171057/tensorflow Page : 1/5\ Suivant: [Page suivante](https://fr.capterra.ca/software/171057/tensorflow?page=2) > Une plateforme open source qui permet aux développeurs, aux entreprises et aux chercheurs de créer et déployer des algorithmes de machine learning. > > Conclusion : 104 utilisateurs lui ont donné la note de **4.6/5**. Figure au meilleur classement pour **Probabilité de recommander le produit**. ----- ## Présentation ### Qui utilise TensorFlow? Plateforme open source sur site et dans le cloud qui permet aux développeurs, aux entreprises et aux chercheurs de créer et déployer des algorithmes et des modèles de machine learning. ## Statistiques et notes | Métrique | Notation | En détail | | **Note globale** | **4.6/5** | 104 Avis | | Simplicité | 3.9/5 | D'après l'ensemble des avis | | Support client | 4.1/5 | D'après l'ensemble des avis | | Rapport qualité-prix | 4.7/5 | D'après l'ensemble des avis | | Fonctionnalités | 4.6/5 | D'après l'ensemble des avis | | Pourcentage de recommandation | 90% | (9/10 Probabilité de recommander le produit) | ## À propos du vendeur - **Entreprise**: Google ## Contexte commercial - **Public cible**: Travailleur autonome, 2–10, 11–50, 51–200, 201–500, 501–1 000, 1 001–5 000, 5 001–10 000, 10 000+ - **Déploiement et plateformes**: Cloud, SaaS, web, Mac (ordinateur), Windows (ordinateur) - **Langues**: anglais - **Pays disponibles**: États-Unis ## Fonctionnalités - Deep learning - Gestion des flux de travail - Modèle de formation - Modélisation prédictive - Traitement automatique du langage naturel ## Ressources d'aide - Service client/courriel - FAQ/forums - Base de connaissances - Support téléphonique ## Category - [Outils d'apprentissage automatique](https://fr.capterra.ca/directory/31103/machine-learning/software) ## Logiciels similaires 1. [Rayven](https://fr.capterra.ca/software/173908/rayven-industrial-business-intelligence) — 5.0/5 (24 reviews) 2. [Google Cloud](https://fr.capterra.ca/software/170983/google-cloud-platform) — 4.7/5 (2262 reviews) 3. [Clickworker](https://fr.capterra.ca/software/175432/clickworker) — 4.3/5 (58 reviews) 4. [Anaconda](https://fr.capterra.ca/software/191760/anaconda) — 4.6/5 (86 reviews) 5. [MySQL](https://fr.capterra.ca/software/11482/mysql) — 4.6/5 (2094 reviews) ## Avis ### "TensorFlow is useful, although it requires a healthy time commitment to produce accurate models" — 4.0/5 > **Thomas** | *26 avril 2018* | Taux de recommandation : 7.0/10 > > **Avantages**: TensorFlow is fascinating in seeing how it produces results in a reasonable time frame. It is completely flexible compared to its costly competitors. The software connects well with various data sources and in setting up scripts to run automatically. > > **Inconvénients**: TensorFlow takes a lot of time to become an expert in what it is doing. The programming time-commitment might not be worth it unless you plan on customizing your modeling to work with other software. > > The benefits I received from this software is more accurate modeling and an interesting insight into what makes one software better than another. TensorFlow did for me what it says it does - produce high quality models, such as neural networks, with a lot of human capital input. ----- ### "Relatively Straightforward Deep Learning Framework" — 5.0/5 > **Ben** | *27 septembre 2019* | Logiciels | Taux de recommandation : 9.0/10 > > **Avantages**: The 2.0 version is easy to set up and there are a lot of APIs that are integrated for using various programming languages to do the same thing. I personally have been using python with this application and have had very little problems getting going. There are a lot of tutorials on getting started, some good data available for free to assist with the learning process. Everything can be run locally which makes it easy to expand on-site. Cloud options are also affordable. > > **Inconvénients**: The learning curve is a bit steep. This isn't specifically an issue because of TensorFlow itself, the idea of neural networks are not simple. TensorFlow has made improvements on 2.0, that make it easier to use compared to previous versions. > > Human pattern recognization, image recognization. Habits and trends. ----- ### "Review of Google Cloud ML Engine" — 3.0/5 > **shushant** | *9 janvier 2021* | Services et technologies de l'information | Taux de recommandation : 7.0/10 > > **Avantages**: The feature of the Google Cloud ML Engine that I most like is the machine learning features that have been provided by this platform. The ML features of this engine provide SOTA results in every task in machine learning and artificial intelligence. The ML features are very handy and easy to use and integrate in other applications as well. I would recommend everyone to use Google Cloud ML Engine for developing AI systems. > > **Inconvénients**: The pricing, when exceeded the free tier of Google Cloud ML platform, is high. The pricing is high compared to other services like Azure Cloud ML platform. > > My overall experience with Google Cloud ML platform was very good. I used it's machine learning services to integrate those in my web applications. ----- ### "Tensorflow powered our internal models for anomaly detection." — 5.0/5 > **Rahul** | *22 juin 2025* | Services et technologies de l'information | Taux de recommandation : 9.0/10 > > **Avantages**: We have employed TensorFlow to build customized models for detecting anomalous patterns in the network logs and user access patterns. Leveraging its python integration and community tutorials, model building and tuning was dead simple. > > **Inconvénients**: The learning curve is steep especially when deploying models at scale or working on performance optimization. The setup becomes pretty daunting if you have little/no ML background. > > TensorFlow has helped us to transition to proactive from reactive security. The end result is that by training our models on our infrastructure data, we are able to detect potential breaches or outliers faster and thereby better protect our network as a whole. ----- ### "A Machine and Deep Learner must have Library" — 5.0/5 > **Scott W.** | *5 septembre 2018* | Conseil en gestion | Taux de recommandation : 10.0/10 > > **Avantages**: This Library is very flexible for doing Matrices and Tensor So building very deep high level but quick and scalable ready to use neural networks is at your finger tips. The added other Anaconda Library and Keras compatibility > > **Inconvénients**: Depreciation of the code is frustrating. To use one form just to throw a Error message. ----- Page : 1/5\ Suivant: [Page suivante](https://fr.capterra.ca/software/171057/tensorflow?page=2) ## Liens - [Afficher sur Capterra](https://fr.capterra.ca/software/171057/tensorflow) ## Cette page est disponible dans les langues suivantes. | Langue | URL | | de | | | de-AT | | | de-CH | | | en | | | en-AE | | | en-AU | | | en-CA | | | en-GB | | | en-IE | | | en-IL | | | en-IN | | | en-NZ | | | en-SG | | | en-ZA | | | es | | | es-AR | | | es-CL | | | es-CO | | | es-CR | | | es-DO | | | es-EC | | | es-MX | | | es-PA | | | es-PE | | | fr | | | fr-BE | | | fr-CA | | | fr-LU | | | it | | | ko | | | nl | | | nl-BE | | | pt | | | pt-PT | | ----- ## Données structurées