---
description: Busca información actualizada sobre TensorFlow. Lee opiniones verificadas y descubre sus funciones, características, precios y usabilidad. Compara TensorFlow con productos similares hasta encontrar la opción adecuada.
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title: TensorFlow: precios, funciones y opiniones | GetApp España 2026
---

Breadcrumb: [Inicio](/) > [Herramientas de machine learning](/directory/1399/machine-learning/software) > [TensorFlow](/software/125283/tensorflow)

# TensorFlow

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> TensorFlow es una plataforma de código abierto que ayuda a los desarrolladores, empresas e investigadores a crear, lanzar y gestionar aplicaciones con aprendizaje automático. La solución ofrece una colección de flujos de trabajo personalizables para ayudar a las organizaciones a desarrollar y entrenar modelos.
> 
> Veredicto: 104 usuarios lo han valorado con **4.6/5**. De los mejores valorados en **Probabilidad de recomendación**.

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## Estadísticas y valoraciones rápidas

| Métrica | Valoración | Detalles |
| **En general** | **4.6/5** | 104 Opiniones |
| Facilidad de uso | 3.9/5 | Basado en las opiniones generales |
| Asistencia al cliente | 4.1/5 | Basado en las opiniones generales |
| Relación calidad-precio | 4.7/5 | Basado en las opiniones generales |
| Funcionalidades | 4.6/5 | Basado en las opiniones generales |
| Porcentaje de recomendaciones | 90% | (9/10 Probabilidad de recomendación) |

## Sobre el proveedor

- **Empresa**: Google

## Contexto comercial

- **Público objetivo**: Trabajador autónomo, 2-10, 11-50, 51-200, 201-500, 501-1.000, 1.001-5.000, 5.001-10.000, 10.000+
- **Despliegue y plataformas**: Cloud, SaaS, Web, Mac (desktop), Windows (desktop)
- **Idiomas admitidos**: inglés
- **Países disponibles**: Estados Unidos

## Funcionalidades

- API
- Aprendizaje profundo
- Flujo de trabajo configurable
- Formación de modelos
- Gestión de flujos de trabajo
- Modelado predictivo
- Procesamiento de lenguaje natural

## Opciones de asistencia

- E-mail/Help Desk
- Preguntas frecuentes/foro
- Base de conocimientos
- Asistencia telefónica

## Categoría

- [Herramientas de machine learning](https://www.getapp.es/directory/1399/machine-learning/software)

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3. [MySQL](https://www.getapp.es/software/1985007/mysql) — 4.6/5 (2094 reviews)
4. [Snowflake](https://www.getapp.es/software/2045875/snowflake) — 4.7/5 (96 reviews)
5. [XLSTAT](https://www.getapp.es/software/2046804/xlstat) — 4.7/5 (398 reviews)

## Opiniones

### "The best deep learning library" — 5.0/5

> **Gaurav** | *25 de junio de 2018* | Valoración de la recomendación: 9.0/10
> 
> **Puntos a favor**: It is best library to wirte models for deep learning.  One advantage is that it is open source.  One of the best thing is that, now it has lots of pre built neural network architecture in it.
> 
> **Desventajas**: This library requires a long learning period, understanding everything in this library is not very easy.
> 
> I have been using this for one and half year, and it's a good learning. And also  efficient to build deep learning models.

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### "Google Cloud ML Engine review" — 5.0/5

> **Usuario verificado** | *14 de noviembre de 2019* | Redes informáticas | Valoración de la recomendación: 9.0/10
> 
> **Puntos a favor**: It doesn't take up any of my local computer resources, just throw a command and let the Google cloud run when I need to run, and it doesn't block any of my other work.&#10;The software provides mainstream training model, prediction model, mainstream ML framework to accelerate the efficiency of our project development.&#10;Low price, suitable for early learning and research.
> 
> **Desventajas**: The threshold of software use is relatively high, and the background of Python or Tensorflow is required, so it is difficult to get started.
> 
> In constructing ML project at first, it is run by the local hardware platform Tensorflow GPU version, so that at the time of training can speed up a lot, but because of the high cost of GPU, when a project order of magnitude increases, the training time of exponential growth, if want to reduce the time, only through optimization algorithm or hardware.After that, I moved the whole project to the cloud platform for operation. Of course, there was also a problem. The resources of Aliyun were all based on fixed configuration to determine different prices.Finally, I migrated to Google Cloud ML Engine, which was cheap and perfectly compatible with other Google products, such as Cloud Storage, Cloud Dataflow, and Cloud Datalab.For the extension of the project and late derivative, provides a great convenience.

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### "TensorFlow - "Google" Solution in an Ocean of Better Solutions" — 3.0/5

> **Zandrich** | *20 de agosto de 2021* | Seguridad informática y de redes | Valoración de la recomendación: 5.0/10
> 
> **Puntos a favor**: TensorFlow has its merits. It's very easily deployable, and allows users to leverage the Machine Learning reportedly used within Google itself. Building models for use in breaking up and learning from large datasets is also relatively simple.
> 
> **Desventajas**: "Open Source" and "Google" do not go hand-in-hand. The service remains ultimately tied to Google, and unless a community begins to use the source to build an independent Machine Learning framework, it's not truly "Open Source", it's just "free to use so we can easily access your data".&#10;&#10;There are better options available, ones that are really Open Source.
> 
> I've used TensorFlow for several years now, but I've done so begrudgingly. My support for Google and their exploitive platforms has waned, and I've begun shifting my attention to other solutions.

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### "Best Library in the Market for Deep Learning\!" — 5.0/5

> **Usuario verificado** | *20 de octubre de 2022* | Servicios de información | Valoración de la recomendación: 10.0/10
> 
> **Puntos a favor**: 1. Easy to understand with a self explanatory syntax 2. Helps you create any kind of deep learning model like CNN ,RNN ,GAN ,etc with ease.3. Support for serving enables you to deploy models as a service4. Free and open source making it first choice to be used in production systems.5. Allows easy monitoring of training using tensorboards
> 
> **Desventajas**: 1. More customization on model architecture can be added2. Frequent version updates leads to changes in the code3. Prior knowledge and training is required for usage
> 
> Its been an amazing journey of using TensorFlow till date, it has enabled me to build and train hundreds of models and deploy them in applications.

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### "Tensorflow is the future of our business, and likely the future of machine learning modeling." — 5.0/5

> **Usuario verificado** | *7 de marzo de 2018* | Software informático | Valoración de la recomendación: 10.0/10
> 
> **Puntos a favor**: Tensorflow is the easiest way to implement machine learning software into your product/business. The repository is colossal and there is an abundance of support within the community alone. Tensorflow is updating regularly and will continue to grow in the years to come.
> 
> **Desventajas**: Hardware is a common bottleneck in machine learning software. We have built out dedicated computing space just for our tensorflow models and will have to continue to upgrade and expand that space. It's just the nature of the business.
> 
> Tensorflow is the future of machine learning modeling. There is no way around that and we as a company are fortunate to bring this technology to the forefront.

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