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Sobre TensorFlow

Biblioteca de aprendizaje de máquinas flexible y de código abierto para investigadores de aprendizaje de máquinas.

Descubre más sobre TensorFlow

Puntos a favor:

The software provides mainstream training model, prediction model, mainstream ML framework to accelerate the efficiency of our project development. Low price, suitable for early learning and research.

Contras:

It is fairly difficult at first, as it brings the whole complexity of working with machine learning. It is very resource-driven and thus the only viable option is using it in the cloud.

Valoraciones de TensorFlow

Evaluación media

Facilidad de uso
3,9
Atención al cliente
4,1
Funcionalidades
4,6
Relación calidad-precio
4,7

Probabilidad de recomendación

8,5/10

TensorFlow tiene una valoración global de 4,6 estrellas sobre 5 según las 103 opiniones de usuarios de Capterra.

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Filtrar opiniones (103)

Scott W.
Scott W.
Deep Learning and Data Engineer en EE. UU.
Usuario de Linkedin verificado
Consultoría de gestión, Trabajador autónomo
Ha utilizado el software durante: Más de dos años
Fuente de la reseña

A Machine and Deep Learner must have Library

5,0 hace 6 años

Puntos a favor:

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

Contras:

Depreciation of the code is frustrating. To use one form just to throw a Error message.

Ben
Software Engineer en EE. UU.
Software informático, 11-50 empleados
Ha utilizado el software durante: 1-5 meses
Fuente de la reseña

Alternativas consideradas:

Relatively Straightforward Deep Learning Framework

5,0 hace 5 años

Comentarios: Human pattern recognization, image recognization. Habits and trends.

Puntos a favor:

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.

Contras:

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.

shushant
shushant
Machine Learning Engineer en Nepal
Usuario de Linkedin verificado
Tecnología y servicios de la información, 51-200 empleados
Ha utilizado el software durante: Más de un año
Fuente de la reseña

Review of Google Cloud ML Engine

3,0 hace 4 años

Comentarios: 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.

Puntos a favor:

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.

Contras:

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.

Thomas
Thomas
Owner, previous CEO en EE. UU.
Usuario de Linkedin verificado
Ha utilizado el software durante: Más de dos años
Fuente de la reseña

TensorFlow is useful, although it requires a healthy time commitment to produce accurate models

4,0 hace 6 años

Comentarios: 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.

Puntos a favor:

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.

Contras:

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.

Esra
Esra
Research and Development Director en Turquía
Usuario de Linkedin verificado
Ha utilizado el software durante: 6-12 meses
Fuente de la reseña

Very helpful in the new world of machine learning.

5,0 hace 6 años

Comentarios: You will learn a lot from TensorFlow. It is a good way of entering the machine learning world.

Puntos a favor:

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.

Contras:

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.

Volodin
Volodin
Freelancer en EE. UU.
Usuario de Linkedin verificado
Software informático, 201-500 empleados
Ha utilizado el software durante: Más de dos años
Fuente de la reseña

Best performance for ML tasks

5,0 hace 6 años

Comentarios: I often work with ML engine, and it appears very complex to me. Because of that I suggest Newbies to start with AutoML first.

Puntos a favor:

ML and AutoML by google dramatically simplify work of Machine Learning developers, in my opinion. Google provides a complete infrastructure that can import export, train and deploy model within the ML environment. On the other hand AutoML provides even more simplicity with operations.

Contras:

It is often difficult to implement ML solution and require time and efforts that are not always available due to certain constraints.

Sean
Sean
Student en Malta
Usuario de Linkedin verificado
Software informático, Trabajador autónomo
Ha utilizado el software durante: Más de un año
Fuente de la reseña

Incredibly powerful

5,0 hace 5 años

Comentarios: The framework has been amazing for me both for getting into machine learning and for developing more advanced projects.

Puntos a favor:

The software is not the easiest to grasp but there are myriad amounts of documentation and examples online which can help with most situations. The Github repo is also well maintained with references to any bugs and problems that one may encounter

Contras:

Debugging is incredibly difficult with version 1 of the framework (this is meant to be addressed in version 2) and can take a long time to get a handle of the particular concepts. The complete library is exhaustive but to the point of abstracting certain concepts too much.

Moustafa Medhat
Moustafa Medhat
Student en Egipto
Usuario de Linkedin verificado
Dispositivos médicos, 10.000+ empleados
Ha utilizado el software durante: Más de un año
Fuente de la reseña

My Review of TensorFlow

4,0 hace 2 años

Comentarios: My overall experience is very good using TensorFlow to develop AI models.

Puntos a favor:

I like that TensorFlow has a version that runs on GPU which is very useful when applying Machine learning. Also, I like that TensorFlow is updated regularly to support different libraries and with new features.I like that TensorFlow supports all the project lifecycle from building and programming to deployment.

Contras:

I don't like that TensorFlow requires expertise as it is not easy for beginners. Also, TensorFlow has a slow speed which is not good in deploying deep learning models compared to other frameworks.

Omkar
Backend developer en India
Tecnología y servicios de la información, 2-10 empleados
Ha utilizado el software durante: 1-5 meses
Fuente de la reseña

Deep learning Bestfriend!

5,0 hace 7 meses

Puntos a favor:

Tensorflow helps me build, train and test models in machine learning and Deep learning. With its commpatibilty to create Deep learning neurons for training purpose and having methods to directly apply it makes tensorflow the best to pursue!!

Contras:

So far tensorflow helps even beginners to use it easily with a number of tutorials and documentations making it less likely to have any thing not to like or havee any complaints to users like me.

Shriya
Shriya
Android Developer en India
Usuario de Linkedin verificado
Tecnología y servicios de la información, 201-500 empleados
Ha utilizado el software durante: Más de un año
Fuente de la reseña

Most advance machine learning library

5,0 hace 6 años

Comentarios: Building machine learning model from scratch and want full power of customisation then choose this tool.

Puntos a favor:

I think it is the most advance library for machine learning specially for deep learning. It very easy to write neural network in this library. It comes with lot of inbuilt function to process data. Also, it has lots of prebuilt function which ease the implementation of neural network.

Contras:

There is no bad thing about this but initially it takes lot of time to understand it as it works on tensors instead of simple vector or array object. But once you learn this, it will be easy to write code.

Aniket
Student en India
Investigación, 501-1.000 empleados
Ha utilizado el software durante: Más de un año
Fuente de la reseña

TensorFlow: The Root of all ML

4,0 hace 3 años

Comentarios: TensorFlow is one of the most powerful frameworks made for machine learning and analysis. It's so powerful that almost all of the other machine learning frameworks are built over TensorFlow or inspired from it. It comes in handy for almost any stage related to Machine Learning, as it houses methods and toolkits to load data, analyze it, visualize results and much more.

Puntos a favor:

TensorFlow is a very powerful framework, and with the new version and the Keras interface, it is 10 times much easier to use, for simple usage. Earlier it used to require a deeper level of understanding to use the library, but now it is very fluid, simple, and at the same time effective.

Contras:

Even though the Keras interface offers a simple way to work with TensorFlow, it is sometimes not possible or convenient to use Keras. Hence, one must fall back to the previous API which is confusing to use sometimes.

Usuario verificado
Usuario de Linkedin verificado
Biotecnología, 10.000+ empleados
Ha utilizado el software durante: Más de un año
Fuente de la reseña

simplicity while being resourceful

5,0 hace 5 años

Comentarios: ability to do machine learning in the cloud with the ability to monitor data quality and also transform data along the way to serve optimal results in ML models.

Puntos a favor:

Simplicity, speed and very low latency of performance are the best parts of google cloud ML. It also has the ability to manage the end to end process in machine learning while also giving the ability to store data and importantly tools to monitor data quality along the ML journey.

Contras:

This is a fully cloud based solution and hence for most optimal performance the data also needs to be in google cloud - I wish there was an on prem version of this product since we are hybrid and have data both on prem and in the cloud.

Khush
Researcher en EE. UU.
Investigación, 51-200 empleados
Ha utilizado el software durante: Más de dos años
Fuente de la reseña

One of the best deep learning libraries

5,0 hace 2 años

Comentarios: Good.

Puntos a favor:

Best library for matrix manipulations and tensor operations. Tensorboard is the best feature.

Contras:

It is difficult it pick up TensorFlow. TensorFlow2 is somewhat easier but there are better options.

Bhargavi
Student en EE. UU.
Software informático, 10.000+ empleados
Ha utilizado el software durante: 6-12 meses
Fuente de la reseña

Rapid prototyping of neural network models which is a great learning resource for students

5,0 hace 6 años

Comentarios: Rich community support and learning resources.

Puntos a favor:

Has rich resources to support and help in learning the nuances of Neural Networks and Deep Learning and helps in rapid initial prototyping

Contras:

Has a steep initial learning curve and is not high level programming system like Pytorch. Would require more effort in defining the the different modules of the project.

Youssef
Data Scientist en Canadá
Software informático, 51-200 empleados
Ha utilizado el software durante: Más de dos años
Fuente de la reseña

Tensorflow AI

5,0 hace 2 años

Comentarios: I have a good experience with Tensorflow. I used it to build many deep learning projects.

Puntos a favor:

Tensorflow 2 is much better than TensorFlow 1. It is easy to use and deploy models.

Contras:

It is hard to build our classes and integrate them with TensorFlow pre-built classes.

Usuario verificado
Usuario de Linkedin verificado
Software informático, 1.001-5.000 empleados
Ha utilizado el software durante: Más de un año
Fuente de la reseña

Machine learning at lightning speed

5,0 hace 5 años

Comentarios: I have used it for various tests, it helps to quickly test a hypothesis. Often when a solution is required on an urgent basis, Cloud ML is the fastest way

Puntos a favor:

I do not need to write a single line of code for running complex ML tasks. All I need, is to adjust a few parameters and provide some data and all the code is taken care of by experts at Google.

Contras:

You need to learn how to use Google Cloud Platform, so that you can integrate it with the database

Usuario verificado
Usuario de Linkedin verificado
Software informático, 10.000+ empleados
Ha utilizado el software durante: 6-12 meses
Fuente de la reseña

Awesome platform to run machine learning

4,0 hace 3 años

Comentarios: Quite satisfied and believe it is an important tool in machine learning used widely over the world.

Puntos a favor:

1. Open source so free of use 2. Can be run on all kinds of platforms 3. Also doesn't need any traditional platform as can be run in Google Cloud Machine 4. Awesome collection of libraries backed by Google 5. Great charts visualization options 6. High performance and scalability

Contras:

1. No Windows support 2. Missing symbolic logic 3. No GPU support for Nvidia

Usuario verificado
Usuario de Linkedin verificado
Marketing y publicidad, 201-500 empleados
Ha utilizado el software durante: 1-5 meses
Fuente de la reseña

Tensorflow for Deep Learning Applications

4,0 hace 5 años

Comentarios: It

Puntos a favor:

Tensorflow is an open source library for deep learning algorithms. In case I had problems with Tensorflow implementation or deployment, I found wide support from the Tensorflow community. Tensorflow comes with tensorboard, which a great tool to visualize the learning process and to track the progress of your application in terms of the accuracy and the gradients.

Contras:

As starting to learn the basic deep learning tools using Tensorflow, I found it not straight forward in terms of the sessions and variables management. It is quite tricky though to debug the code if it has some problems. Also, TesnorFlow does not support dynamic graphs. It was not an issue for me in the beginning, however, it started to be a challenging problem while dealing with dynamic graphs (e.g. text modeling).

Arun
Teacher en Emiratos Árabes Unidos
Administración educativa, 201-500 empleados
Ha utilizado el software durante: 1-5 meses
Fuente de la reseña

Feedback

5,0 hace 10 meses

Comentarios: good product

Puntos a favor:

easy to use. good performance .integration with python is easy

Contras:

expensive. AI tools need to be more graphically represented

Vibhor
Researcher en EE. UU.
Investigación, 5.001-10.000 empleados
Ha utilizado el software durante: 6-12 meses
Fuente de la reseña

Great for scaling your Machine Learning needs

5,0 hace 4 años

Comentarios: Great for anyone starting to use ML as a analytical tool. It provides nee=cessary training for you to move forward

Puntos a favor:

Ease of use, adaptability, and speed associated with the cloud platform is amazing. It can help solve any research problems

Contras:

It uses standard template whcih might be difficult to customize in special needs scenario. Some odf the functionality is locked out limiting usage

Arwildo
Arwildo
Student en Indonesia
Usuario de Linkedin verificado
Investigación, 1.001-5.000 empleados
Ha utilizado el software durante: 1-5 meses
Fuente de la reseña

The best powerfull libary for your neural network

5,0 hace 5 años

Comentarios: I use Tensorflow to design my first code in machine learning to build an autopilot car game.

Puntos a favor:

Tensorflow it's easy to set up and provides a simple way to start learning machine learning with a guides tutorial that comes with data that needed to train the algorithm.

Contras:

It does not available to a 32bit machine, you need 64bit.

Jamie
Software Developer en Sudáfrica
Software informático, 51-200 empleados
Ha utilizado el software durante: 6-12 meses
Fuente de la reseña

Becoming the standard for Machine Learning tasks

5,0 hace 5 años

Puntos a favor:

Support for GPU acceleration. A huge number of tutorials/resources. Many different algorithms to choose from and very flexible.

Contras:

Requires significant expertise--not a simple piece of software. Development largely controlled by one company--Google.

Gaurav
Gaurav
Software Developer en India
Usuario de Linkedin verificado
, 201-500 empleados
Ha utilizado el software durante: Más de un año
Fuente de la reseña

The best deep learning library

5,0 hace 6 años

Comentarios: I have been using this for one and half year, and it's a good learning. And also efficient to build deep learning models.

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.

Contras:

This library requires a long learning period, understanding everything in this library is not very easy.

SAMUEL
SAMUEL
Trainee en Nigeria
Usuario de Linkedin verificado
Salud, bienestar y deporte, 51-200 empleados
Ha utilizado el software durante: 6-12 meses
Fuente de la reseña

Excellent Software

5,0 hace 6 años

Puntos a favor:

User friendly. Great features and functionalities. Availability of tracking bug. The software shows CPU usage.

Contras:

The CPU usage is only available in percentage.

Swetha
Student en EE. UU.
Ha utilizado el software durante: 1-5 meses
Fuente de la reseña

If you want to visualize your deep learning , this is the place to visit

5,0 hace 6 años

Puntos a favor:

It is essentially the best machine learning and deep learning software. You get to visualize what you are doing with their dashboard visualizer which is basically google analytics for deep learning. I fell in love with Deep learning because of tensorflow.

Contras:

I had a little difficulty with setting up the working environment as it acts as a server and shows the visualization in the browsers local host.