--- description: Detaillierte Informationen über TensorFlow zu Benutzerfreundlichkeit, Funktionen, Kosten, Vor- und Nachteilen aus verifizierten Nutzer-Erfahrungen. Lies Ratings & Bewertungen und entdecke ähnliche Tools dank Capterra Austria. image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: TensorFlow Kosten, Erfahrungen & Bewertungen - Capterra Österreich 2026 --- Breadcrumb: [Startseite](/) > [Machine Learning Software](/directory/31103/machine-learning/software) > [TensorFlow](/software/171057/tensorflow) # TensorFlow Canonical: https://www.capterra.at/software/171057/tensorflow Seite: 1 / 5\ Zurück: [Nächste Seite](https://www.capterra.at/software/171057/tensorflow?page=2) > Flexible Open-Source-Bibliothek für maschinelles Lernen für Forscher im Bereich des maschinellen Lernens. > > Bewertung: **4.6/5** von 104 Nutzern. Top bewertet für **Weiterempfehlungsquote**. ----- ## Kurzstatistiken und Ratings | Metrik | Bewertung | Detail | | **Gesamt** | **4.6/5** | 104 Nutzerbewertungen | | Bedienkomfort | 3.9/5 | Auf Basis der Gesamtbewertungen | | Kundenbetreuung | 4.1/5 | Auf Basis der Gesamtbewertungen | | Preis-Leistungs-Verhältnis | 4.7/5 | Auf Basis der Gesamtbewertungen | | Funktionen | 4.6/5 | Auf Basis der Gesamtbewertungen | | Empfehlungsprozentsatz | 90% | (9/10 Weiterempfehlungsquote) | ## Über den Anbieter - **Unternehmen**: Google ## Gewerblicher Kontext - **Zielgruppe**: Selbstständig, 2–10, 11–50, 51–200, 201–500, 501–1 000, 1 001–5 000, 5 001–10 000, 10 000+ - **Bereitstellungen und Plattformen**: Cloud, SaaS, webbasiert, Mac (Desktop), Windows (Desktop) - **Unterstützte Sprachen**: Englisch - **Verfügbare Länder**: Vereinigte Staaten ## Funktionen - Deep Learning Software - Modell-Training - Prädiktives Modellieren - Verarbeitung natürlicher Sprache - Workflow-Management ## Optionen für Kundensupport - E-Mail/Helpdesk - FAQ/Forum - Wissensdatenbank - Telefon-Support ## Category - [Machine Learning Software](https://www.capterra.at/directory/31103/machine-learning/software) ## Alternativen 1. [Rayven](https://www.capterra.at/software/173908/rayven-industrial-business-intelligence) — 5.0/5 (24 reviews) 2. [Google Cloud](https://www.capterra.at/software/170983/google-cloud-platform) — 4.7/5 (2262 reviews) 3. [Clickworker](https://www.capterra.at/software/175432/clickworker) — 4.3/5 (58 reviews) 4. [Anaconda](https://www.capterra.at/software/191760/anaconda) — 4.6/5 (86 reviews) 5. [MySQL](https://www.capterra.at/software/11482/mysql) — 4.6/5 (2094 reviews) ## Nutzerbewertungen ### "TensorFlow is useful, although it requires a healthy time commitment to produce accurate models" — 4.0/5 > **Thomas** | *26. April 2018* | Empfehlungsbewertung: 7.0/10 > > **Vorteile**: 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. > > **Nachteile**: 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. September 2019* | Computer-Software | Empfehlungsbewertung: 9.0/10 > > **Vorteile**: 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. > > **Nachteile**: 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. Jänner 2021* | Informationstechnologie & -dienste | Empfehlungsbewertung: 7.0/10 > > **Vorteile**: 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. > > **Nachteile**: 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. Juni 2025* | Informationstechnologie & -dienste | Empfehlungsbewertung: 9.0/10 > > **Vorteile**: 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. > > **Nachteile**: 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. September 2018* | Unternehmensberatung | Empfehlungsbewertung: 10.0/10 > > **Vorteile**: 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 > > **Nachteile**: Depreciation of the code is frustrating. To use one form just to throw a Error message. ----- Seite: 1 / 5\ Zurück: [Nächste Seite](https://www.capterra.at/software/171057/tensorflow?page=2) ## Links - [Auf Capterra anzeigen](https://www.capterra.at/software/171057/tensorflow) ## Diese Seite ist in den folgenden Sprachen verfügbar | Sprache | 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 | | ----- ## Strukturierte Daten