--- 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 Schweiz. image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: TensorFlow Kosten, Erfahrungen & Bewertungen - Capterra Schweiz 2026 --- Breadcrumb: [Startseite](/) > [Machine Learning Software](/directory/31103/machine-learning/software) > [TensorFlow](/software/171057/tensorflow) # TensorFlow Canonical: https://www.capterra.ch/software/171057/tensorflow Seite: 1 / 5\ Weiter: [Nächste Seite](https://www.capterra.ch/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.ch/directory/31103/machine-learning/software) ## Alternativen 1. [Rayven](https://www.capterra.ch/software/173908/rayven-industrial-business-intelligence) — 5.0/5 (24 reviews) 2. [Clickworker](https://www.capterra.ch/software/175432/clickworker) — 4.3/5 (58 reviews) 3. [Google Cloud](https://www.capterra.ch/software/170983/google-cloud-platform) — 4.7/5 (2284 reviews) 4. [Anaconda](https://www.capterra.ch/software/191760/anaconda) — 4.6/5 (86 reviews) 5. [Snowflake](https://www.capterra.ch/software/148267/snowflake) — 4.7/5 (96 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. Januar 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. ----- ### "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. ----- ### "Very helpful in the new world of machine learning." — 5.0/5 > **Esra** | *11. Mai 2018* | Empfehlungsbewertung: 9.0/10 > > **Vorteile**: I used TensorFlow on AWS which was easier with all the infrastructure AWS built. It was a good start to machine learning with all the AI and neural network popularity going on these days. It was challenging and exciting to prepare datasets, train them and see the satisfactory results in dashboard. It is also open source and this gives an advantage to TensorFlow. > > **Nachteile**: There is a long and challenging learning period. Documentation is rich but it would be so much better to learn and use it with some visual aids. > > You will learn a lot from TensorFlow. It is a good way of entering the machine learning world. ----- Seite: 1 / 5\ Weiter: [Nächste Seite](https://www.capterra.ch/software/171057/tensorflow?page=2) ## Links - [Auf Capterra anzeigen](https://www.capterra.ch/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