# TensorFlow Reviews **Vendor:** TensorFlow **Category:** [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) **Average Rating:** 4.5/5.0 **Total Reviews:** 138 ## About TensorFlow TensorFlow is an open-source machine learning library developed by the Google Brain Team, designed to facilitate the creation, training, and deployment of machine learning models across various platforms. It provides a comprehensive ecosystem that supports tasks ranging from simple data flow graphs to complex neural networks, enabling developers and researchers to build and deploy machine learning applications efficiently. Key Features and Functionality: - Flexible Architecture: TensorFlow's architecture allows for deployment across multiple platforms, including CPUs, GPUs, and TPUs, and supports various operating systems such as Linux, macOS, Windows, Android, and JavaScript. - Multiple Language Support: While primarily offering a Python API, TensorFlow also provides support for other languages, including C++, Java, and JavaScript, catering to a diverse developer community. - High-Level APIs: TensorFlow includes high-level APIs like Keras, which simplify the process of building and training models, making machine learning more accessible to beginners and efficient for experts. - Eager Execution: This feature allows for immediate evaluation of operations, facilitating intuitive debugging and dynamic graph building. - Distributed Computing: TensorFlow supports distributed training, enabling the scaling of machine learning models across multiple devices and servers without significant code modifications. Primary Value and Solutions Provided: TensorFlow addresses the challenges of developing and deploying machine learning models by offering a unified, scalable, and flexible platform. It streamlines the workflow from model conception to deployment, reducing the complexity associated with machine learning projects. By supporting a wide range of platforms and languages, TensorFlow empowers users to implement machine learning solutions in diverse environments, from research labs to production systems. Its comprehensive suite of tools and libraries accelerates the development process, fosters innovation, and enables the creation of sophisticated models that can tackle real-world problems effectively. ## TensorFlow Pros & Cons **What users like:** - Users appreciate the **flexibility and power** of TensorFlow, making it ideal for various machine learning projects. (23 reviews) - Users appreciate the **AI integration** of TensorFlow, benefiting from its end-to-end interface and powerful capabilities. (19 reviews) - Users find **TensorFlow's ease of use** makes model building simple and efficient with excellent community support. (19 reviews) - Users value the **variety of models** offered by TensorFlow, enhancing flexibility in their machine learning projects. (18 reviews) - Users appreciate the **scalability** of TensorFlow, enabling efficient distributed training across various hardware platforms. (14 reviews) - Users value the **excellent customer support** and community of TensorFlow, enhancing their machine learning project experience. (13 reviews) - Users appreciate the **easy integrations** of TensorFlow, facilitating seamless use across various platforms and applications. (13 reviews) - Flexibility (12 reviews) - Coding Ease (8 reviews) - Integrated Platform (7 reviews) **What users dislike:** - Users note the **steep learning curve** of TensorFlow, making initial development challenging, especially for beginners. (25 reviews) - Users find TensorFlow's **complexity** challenging, especially when converting models and debugging, making it hard to learn. (8 reviews) - Users find the **difficult learning** curve of TensorFlow challenging, especially with Keras and frequent API changes. (8 reviews) - Users find **error handling difficult** , as complex messages and poor stack traces complicate debugging efforts. (6 reviews) - Users often face **slow performance** with TensorFlow, especially when executing complex models or during large training tasks. (6 reviews) - Software Bugs (5 reviews) - Confusing Syntax (3 reviews) - Difficult Setup (3 reviews) - Insufficient Learning Resources (3 reviews) - Limited Resources (3 reviews) ## TensorFlow Reviews ### 1. Mechanical engineering PhD student who used TensorFlow in his research. **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.) **Reviewed Date:** August 05, 2020 **What do you like best about TensorFlow?** Rapid prototyping. Especially in building a neural network. **What do you dislike about TensorFlow?** The documentation some times don't have plenty of examples for different scenarios **What problems is TensorFlow solving and how is that benefiting you?** Chemical reactions in materials. ### 2. Most powerful machine learning framework to train model. **Rating:** 5.0/5.0 stars **Reviewed by:** Radhika D. | Product Engineer, Computer Software **Reviewed Date:** August 05, 2019 **What do you like best about TensorFlow?** Three different crowds use Tensorflow : Researcher , data scientist and developer. Ideally they there were no so such which can collaborate three of them and provide better efficiency. Tensorflow was the solution they created to solve this problem. The library was to scale, it was made to run on multiple CPU's or GPU's and even mobile OS and it has several wrappers. From installation to deployment Tensorflow is the easiest among all the other platform which provide cross cross-platform deployment. Tensorflow provide decent event handling, graph management, image management and best feature is tensorboard. **What do you dislike about TensorFlow?** Tensorflow is powerful in terms of performance but with less area to work with. It will restrict you from as tweaking of algorithms in it is quite a complex task. Since the release of Tensorflow 2.0, tensorflow has gain leverage over other framework but its community is still growing and sometime its very hard to find answers when you are stuck in your work. **What problems is TensorFlow solving and how is that benefiting you?** For model training and mostly we have used tensorflow as it provide multiple platform deployment. ### 3. An awesome human readable machine learning framework **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** July 15, 2019 **What do you like best about TensorFlow?** Tensorflow is free, it's easy to install and get running and also light weight. Best of all Tensorflow is human readable, Unlike most of the other deep learning frameworks out there that make life difficult. Tensorflow is built by Google and integrates seamlessly into all of their existing products making deployments very easy. It's also very fast and efficient backend for models. **What do you dislike about TensorFlow?** Like all deep learning frameworks, it requires lots of data to train a network built using it but this is hardly surprising **Recommendations to others considering TensorFlow:** With Tensorflow, you can quickly build your machine learning frameworks. It's properly documented and is very easy to use **What problems is TensorFlow solving and how is that benefiting you?** I've been able to rapidly develop and deploy several machine learning and deep learning models. Tensorflow also allowed me to accomplish AI related tasks that were previously out of my reach due to the cost of other deep learning frameworks ### 4. Tensorflow Deep learning framework **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Telecommunications | Enterprise (> 1000 emp.) **Reviewed Date:** January 02, 2020 **What do you like best about TensorFlow?** Tensorflow is the package available in python for creating neural network. Best part of tensor flow is we can create the complex machine learning model in just few lines of code. **What do you dislike about TensorFlow?** Sometimes i feel as complexity of the data increases, speed is the concern. it takes more time. **Recommendations to others considering TensorFlow:** It is one of the best way to train test and develope your neural network in few line of codes. **What problems is TensorFlow solving and how is that benefiting you?** I use to create complex machine learning model and creating deep neural networks for my some tasks. ### 5. building a CNN for my Data **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** November 19, 2019 **What do you like best about TensorFlow?** lots of my peers and university use this so lots of examples **What do you dislike about TensorFlow?** It should have code expansions for some funtions to keep cleaner code **Recommendations to others considering TensorFlow:** It's necessary in my profession **What problems is TensorFlow solving and how is that benefiting you?** developing a ML model for my data, wrote a CNN for my Data ### 6. TensorFlow Review **Rating:** 4.5/5.0 stars **Reviewed by:** Aanu B. | Assistant Consultant, Small-Business (50 or fewer emp.) **Reviewed Date:** July 10, 2019 **What do you like best about TensorFlow?** - It is easy to use (for adept users) - It is more often used for research, this gives TensorFlow regular support and updates. - It is the back-end for one of the easiest frameworks (Keras) **What do you dislike about TensorFlow?** - It is hard to learn (for beginners in AI) **What problems is TensorFlow solving and how is that benefiting you?** I use TensorFlow to build deep learning models for object detection and image classification. ### 7. TensorFlow Worth the Learning Curve **Rating:** 5.0/5.0 stars **Reviewed by:** Andrew C. | Digital Signal Processing Engineer, Defense & Space, Enterprise (> 1000 emp.) **Reviewed Date:** October 12, 2018 **What do you like best about TensorFlow?** I like how easy TensorFlow makes building ML models without sacrificing low-level implementation capabilities. It includes a wide variety of prebuilt models and model subblocks that can be plugged together using simple python scripts. Tensorflow handles the implementation details seamlessly allows you to abstract away the underlying hardware, be they GPU's, CPU's or TPU's. We don't have to think about what kind of convolution algorithm we're using unless we absolutely want to. The data ingestion pipeline makes handling hundreds of GB of data a simple task. No more loading everything into RAM or worrying about file access and formatting. It does come with a price and it isn't as intuitive as it could be but it is well worth learning if you are serious about applied machine learning or just experimenting. **What do you dislike about TensorFlow?** I dislike the define-and-run model of TensowFlow. It is unintuitive and occasionally lends itself to clunky solutions. It differs from the define-by-run model of the other major ML frameworks which is a barrier to access for many. I also dislike the structure of variables as tensors. It is often unclear whether your variables need to be tensors or plain python types. Once you get the hang of using TensorFlow it becomes obvious but something as simple as variable definitions shouldn't be so opaque. **Recommendations to others considering TensorFlow:** It is worth the learning curve. Google has a fantastic introductory series on both Machine Learning and TensorFlw specifically that I highly recommend. **What problems is TensorFlow solving and how is that benefiting you?** We are building models using Tensorflow that can learn from our datasets to accurately classify samples. Previously, building these models required highly domain specific knowledge were built in an ad hoc way for each class of data. Tensorflow allows us to build one model that can be far more easily adapted and changed. ### 8. Tensorflow 2.0 **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** June 28, 2019 **What do you like best about TensorFlow?** Tensorflow transformed to the best deep learning framework since tensorflow 2.0 it's faster new functionalities and it uses both a dynamic and static flow graph which makes it good for both production and testing **What do you dislike about TensorFlow?** I don't really see what I dislike about tensorflow 2.0 it's got everything ready except that it's not so easy to learn **Recommendations to others considering TensorFlow:** I recommend tensor flow to companies that are into machine learning and artificial intelligence it's a good API for these things **What problems is TensorFlow solving and how is that benefiting you?** I used tensorflow in most of my machine learning competitions to create machine learning models mostly image classification models ### 9. Using it on daily basis **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** October 02, 2019 **What do you like best about TensorFlow?** I like it's new version 2.0 because they include keras workflow with TF and distributed computing. **What do you dislike about TensorFlow?** I dislike the most it that it low level API, we have to define placeholders, session. **What problems is TensorFlow solving and how is that benefiting you?** Deep Learning can't be easy without Tensorflow and keras. ### 10. Excellent library for Deep Learning **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Research | Mid-Market (51-1000 emp.) **Reviewed Date:** April 25, 2019 **What do you like best about TensorFlow?** The intuitive way in which all the methods interact. It is an extremely user friendly wrapper for deep learning projects and research. Enables quick prototyping of the models. **What do you dislike about TensorFlow?** There are major changes coming. People might have to relearn some of the ways in which to use the library. With each update there are some really annoying deprecation warnings. **Recommendations to others considering TensorFlow:** It is a great tool to prototype models for research and projects. However, with all the deprecation warnings happening, it might be better to learn Keras. **What problems is TensorFlow solving and how is that benefiting you?** I have been using TensorFlow extensively for all my projects in my graduate level Deep Learning course. I even use it for my research. ### 11. If you do machine learning... **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Enterprise (> 1000 emp.) **Reviewed Date:** August 08, 2019 **What do you like best about TensorFlow?** Pretty much won the battle of what library to use for machine learning problems. Has everything you need for foundational building blocks of large scale calculations **What do you dislike about TensorFlow?** Not much in the way of cons as everyone is using tensorflow. A little difficult to set up with a gpu **Recommendations to others considering TensorFlow:** Use it for any machine learning problems! **What problems is TensorFlow solving and how is that benefiting you?** Machine learning problems ### 12. Too messy **Rating:** 3.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** May 25, 2019 **What do you like best about TensorFlow?** The static computational graph is a very good concept. The API usually has implementations available for almost everything you would need. **What do you dislike about TensorFlow?** The documentation is not very good. The API is too messed up - there are several functions that do the same thing with minor differences and little documentation about the differences. Boilerplate code is also usually long. The API is cumbersome to use overall. **What problems is TensorFlow solving and how is that benefiting you?** I have used tensorflow for several projects related to text classification. ### 13. My experience with Tensorflow as a grad student **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** February 17, 2019 **What do you like best about TensorFlow?** Heavy machine learning models can be built on top of the optimized deep learning models integrated by Tensorflow. Compatibility with other frameworks makes it possible to optimize on the production level. **What do you dislike about TensorFlow?** The models can be a little heavier to deploy in mobile applications when the question is of limited space. Thus the execution is also slow. If Google can divide them into several modules making space changes depending on the device. **What problems is TensorFlow solving and how is that benefiting you?** In our organization, we used variations of the TensorFlow Inception model mainly for image classification and image categorization of randomized data to compare performance with other libraries in order to publish our research. ### 14. Amazing library if you are expert in machine learning, **Rating:** 4.0/5.0 stars **Reviewed by:** Ahmad A. | Research Assistant , Small-Business (50 or fewer emp.) **Reviewed Date:** November 04, 2018 **What do you like best about TensorFlow?** It is amazingly fast, It works in parallel, and supports GPU **What do you dislike about TensorFlow?** The idea of Tensors is not very well explained in the official website, and that makes the user to panic if they do not understand the most basic idea of it after an hour of digging **Recommendations to others considering TensorFlow:** Do not get disapointed if you are difficulties mastering this library, once you know how to correctly use it, the creating fantastic machine learning models will be fun and easy **What problems is TensorFlow solving and how is that benefiting you?** I am a researcher and an engineer, I combine my Machine learning knowledge with the use of TensorFlow to apply it to real life engineering applications ### 15. Write Neural Networks in under 50 lines **Rating:** 5.0/5.0 stars **Reviewed by:** Lucifer M. | Freelance Web Developer **Reviewed Date:** November 29, 2018 **What do you like best about TensorFlow?** - Tensorflow is one of the best frameworks to do deep learning, machine learning for huge datasets. - The dataset can have millions of records can be of terabytes in size **What do you dislike about TensorFlow?** - Tensorflow can be slow when working with large files. A GPU might be required to help with the processing **What problems is TensorFlow solving and how is that benefiting you?** I created a neural network on CDC sources datasets to run predictions. Once I worked on many diseases and created individual model, I developed a predictive model platform to run several neural networks at once for multiple diseases. ### 16. Easy implementation of neural networks **Rating:** 4.5/5.0 stars **Reviewed by:** Tanmayan P. | Volunteer Student Researcher, Small-Business (50 or fewer emp.) **Reviewed Date:** February 12, 2019 **What do you like best about TensorFlow?** Most of the functionality is abstracted to a very high level. For example, I just need to run the optimizer.optimize() command to Backpropagate over my entire network **What do you dislike about TensorFlow?** Sometimes, debugging is very difficult, as unless a TF.session is started, we cannot see the variable values **What problems is TensorFlow solving and how is that benefiting you?** Neural network design and testing new algorithms ### 17. Explore ia **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Mining & Metals | Enterprise (> 1000 emp.) **Reviewed Date:** May 20, 2019 **What do you like best about TensorFlow?** It s open source, and very hse full in deeplearning **What do you dislike about TensorFlow?** Some complixity it's hard for biginner to use it **What problems is TensorFlow solving and how is that benefiting you?** Image classification ### 18. fast, reliable, and amazing machine learning library **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Research | Enterprise (> 1000 emp.) **Reviewed Date:** November 09, 2018 **What do you like best about TensorFlow?** It covers a wide range of Machine learning problems, superviesd, unsupervised, reinforcment ... learning very fast possible to run in parallet **What do you dislike about TensorFlow?** for beginners it can be very confusing and they can easily stuck in the different pages of official tutorial I beleive the toturial could use some introductory videos **What problems is TensorFlow solving and how is that benefiting you?** machine learning application in engineering problems, we solve energy engineering problems with the help of ML using Tensorflow ### 19. very intuitive and powerful platform. **Rating:** 5.0/5.0 stars **Reviewed by:** james t. | Sr Manager - Legal, GRC, and Chemicals Mgmt, Mid-Market (51-1000 emp.) **Reviewed Date:** November 28, 2018 **What do you like best about TensorFlow?** Offers great platform to develop in the AI domain to deliver business value efficiently. **What do you dislike about TensorFlow?** None at this time, as we are still in POC. **What problems is TensorFlow solving and how is that benefiting you?** AI proof of concept in the legal and compliance space to help formulate AI strategy. ### 20. Great library for performing deep learning **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Semiconductors | Enterprise (> 1000 emp.) **Reviewed Date:** November 28, 2018 **What do you like best about TensorFlow?** Great documentation written by Google's Tensorflow Team, and a lot of community engagement. Most answers regarding Tensorflow have answers available from the community. **What do you dislike about TensorFlow?** Library interface is a bit lower-level compared to other Python interfaces like Keras, but developer experience has been improving. **Recommendations to others considering TensorFlow:** Useful for deep learning. **What problems is TensorFlow solving and how is that benefiting you?** Performing supervised learning on business problems requiring predictions. We have realized cost savings using the results of our predictions. ### 21. TensorFlow Review **Rating:** 5.0/5.0 stars **Reviewed by:** Banjo O. | Senior Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** November 28, 2018 **What do you like best about TensorFlow?** Lots of things you can do for creating models **What do you dislike about TensorFlow?** Very complex, has there are alot of manual steps **What problems is TensorFlow solving and how is that benefiting you?** Machine Learning in the cloud ### 22. A powerful deep learning library, with certain rough edges **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** July 25, 2018 **What do you like best about TensorFlow?** Automatic differentiation and support for backpropagation through many useful mathematical operations. Tensorboard interface for monitoring and visualisation. **What do you dislike about TensorFlow?** The programming model is somewhat cumbersome, and reliant on global state behind the scenes. For any task there seems to be multiple incompatible ways of achieving it, with varying degrees of documentation. The API is a mess, with many different high level interfaces. There is no standardised workflow, which makes mixing and matching models from different sources very difficult. **Recommendations to others considering TensorFlow:** Carefully consider the alternatives, such as PyTorch which can be easier for development by specifically targeting Python and the Pythonic way of programming (although potentially at the expense of flexibility). **What problems is TensorFlow solving and how is that benefiting you?** Training deep learning models for video analysis. After the initial hurdles, it does the job. ### 23. Powerful machine learning library! **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Services | Small-Business (50 or fewer emp.) **Reviewed Date:** June 14, 2018 **What do you like best about TensorFlow?** Tensorflow is an extremely powerful library whose users can use it for classification, regression, or any number of complex neural network models, such as GANs and CNNs. It can also be used as a backend to Keras or other higher level libraries. **What do you dislike about TensorFlow?** The API leaves something to be desired, as it can get quite complex and messy as you write more code. It is pertinent that organization of the code is better handled. As well, for very large applications, it may be slower than competing libraries such as Torch. **Recommendations to others considering TensorFlow:** Learn deep learning first as the API is extremely specific to those in the field of AI. **What problems is TensorFlow solving and how is that benefiting you?** We use it to create classification and regression pipelines for our clients, such as with agricultural yield prediction. ### 24. Machine Learning Trend **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** January 08, 2019 **What do you like best about TensorFlow?** 1: Broad libraries 2: Support 3: Documentation **What do you dislike about TensorFlow?** 1: Example that the tutorial use. 2: Tutorial. **What problems is TensorFlow solving and how is that benefiting you?** I use TensorFlow for analyze data. ### 25. applicability of tensor flow for research purposes **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Biotechnology | Small-Business (50 or fewer emp.) **Reviewed Date:** November 27, 2018 **What do you like best about TensorFlow?** the models covered by tensor flow are great for research purboses and the examples provided are good **What do you dislike about TensorFlow?** more examples which covers several research fields could be covered **What problems is TensorFlow solving and how is that benefiting you?** researcgh at university related to prediciting students behaviour ### 26. best one out there **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Farming | Enterprise (> 1000 emp.) **Reviewed Date:** October 06, 2018 **What do you like best about TensorFlow?** the Tensor flow API is the best and the model created on the desktop can be used any where. And the availability of pre trained models is anothe rbest part. **What do you dislike about TensorFlow?** Little hard for the non coding person to train and create models. **Recommendations to others considering TensorFlow:** Should develop a UI for deploying new models and training them. **What problems is TensorFlow solving and how is that benefiting you?** ML and predictions ### 27. Great tool, worth the steep learning curve **Rating:** 4.5/5.0 stars **Reviewed by:** Raul G. | Small-Business (50 or fewer emp.) **Reviewed Date:** October 19, 2017 **What do you like best about TensorFlow?** With TensorFlow you can do pretty much anything you want in the broad area of machine learning. But the amazing thing about it is that you can also use this software to deal with math problems outside of machine learning. The use of computation graphs along with TensorBoard makes model visualization very intuitive. **What do you dislike about TensorFlow?** The learning curve can be quite steep if, like me, you start with no knowledge of TensorFlow's computational model philosophy. Once you get the hang of things, it can be quite rewarding. Also, as the software is updated quite frequently, it seems the documentation is not as accurate as it could be, leading to quite a few headaches. **Recommendations to others considering TensorFlow:** Be VERY patient. It may look a bit overwhelming, but it is an amazing tool to master and a great philosophy of computation to understand and follow. **What problems is TensorFlow solving and how is that benefiting you?** I am working with time series forecasting models, and TensorFlow allows for pretty fast prototyping while allowing a huge degree of freedom in terms of model features that you can incorporate. ### 28. A short path into artificial intelligence **Rating:** 5.0/5.0 stars **Reviewed by:** Derek P. | Small-Business (50 or fewer emp.) **Reviewed Date:** April 26, 2018 **What do you like best about TensorFlow?** TensorFlow is a platform that is very easy to learn yet hard to master. Due to a heavy amounts of code samples it is very easy to dive head first into Artificial Intelligence **What do you dislike about TensorFlow?** Though very thorough TensorFlow documentation can feel very overwhelming. **Recommendations to others considering TensorFlow:** Dont rush into it, take it slow and under the information **What problems is TensorFlow solving and how is that benefiting you?** I have incorporated tensorflow into my image classifing solutions. Due to the compatibility for android and IOS devices tensorflow is incorporated into many of our apps ### 29. The machine learning swiss army knife **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** January 30, 2018 **What do you like best about TensorFlow?** The ability to easily write code that scales up to multiple CPUs/GPUs. Since version 1.0, there are higher level modules that provide Keras-like functionalities (e.g. layers, metrics). Moreover, it is definitely production ready. The best thing, though, is the Tensorboard tool that can be used to debug the implemented algorithms. **What do you dislike about TensorFlow?** Setting up GPU support on Windows can be tricky, depending on how convoluted the environment is. While Tensorboard is a great tool, sometimes its pages get "stuck" and force to reload the tensorboard server again. The learning curve might be steeper than Keras, which hides most of the complexity away. **Recommendations to others considering TensorFlow:** I'd strongly suggest using Keras for prototyping before jumping straight into TensorFlow. Getting started with keras is much simpler and paves the way to implementing the final product with TensorFlow. **What problems is TensorFlow solving and how is that benefiting you?** TensorFlow it's a nice, low/mid level API to build production-level software that deals with machine learning. It's stable, so building products at scale for production use is not a problem. This is being used as the back-end to train voice recognition models. ### 30. Deep learning made easy with TensorFlow **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** October 06, 2017 **What do you like best about TensorFlow?** The ease of building deep learning models and the high level API's. One can build all kind of architectures pertaining to deep learning. One can use it to build models to solve computer vision problems, perform speech analytics, text analytics, seq2seq models. It supports major algorithms such as ConvNets, RNN, LSTMs, Seq2Seq, It also includes some of the pretrained models which can be customized and trained with new datasets. It can also scale to use multi -gpu systems out of the box without much configuration. **What do you dislike about TensorFlow?** Some of the benchmark results show it doesn't train fast, I hope the team is working on making it faster. Also it doesn't include other ML models for comparison. **Recommendations to others considering TensorFlow:** It has good documentation, and there are many online courses to train the resources. There are new features being added regularly and has great flexibility in terms of use common API's and if needed one can make use of computational graphs to build and customize the models as per the need. **What problems is TensorFlow solving and how is that benefiting you?** We are trying to use multi-layer neural network in customer analytics space. We use various models and TensorFlow is easy to implement using high level api. Personally, I have used it in building forecasting models, sentiment analysis, text analytics, language translation, general adversarial networks. The implementation for all the models were very easy and it provided great benefits in terms of using multi-gpu systems efficiently. ### 31. Really good for AI/ML based use cases **Rating:** 4.0/5.0 stars **Reviewed by:** Krishnan V. | Chief Sales Officer, Information Services, Mid-Market (51-1000 emp.) **Reviewed Date:** February 01, 2018 **What do you like best about TensorFlow?** Helps setting up the neural network well - strongly recommend it We have been using internally and evaluating how to use it. **What do you dislike about TensorFlow?** Don't really dislike anything in it - maybe more flexibility **Recommendations to others considering TensorFlow:** Decide what are the use cases before taking up the platform. Fairly intuitive and easy to use **What problems is TensorFlow solving and how is that benefiting you?** - Better time to market - Easier to deploy solutions in the market - Develop newer capabilities ### 32. Simple way to build complex models **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** February 01, 2018 **What do you like best about TensorFlow?** I like how easy tensor flow makes it to build a simple neural network. You can have a model up and running in minutes, but tensorflow still provides advanced users with the ability to customize models a lot. **What do you dislike about TensorFlow?** I wish that the documentation for tensorflow was more detailed. Sometimes I have a hard time finding answers to some questions that I have about tensorflow. **What problems is TensorFlow solving and how is that benefiting you?** I am trying to make more accurate predictive models in the credit industry. Tensorflow has helped to improve the accuracy of existing models built using other software by a few percent. ### 33. Best deep learning open source library out there **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Medical Devices | Small-Business (50 or fewer emp.) **Reviewed Date:** January 24, 2018 **What do you like best about TensorFlow?** TensorFlow uses python which is conenient.Its numerical compability with NumPy is great. We can store the models and reuse them is very convenient **What do you dislike about TensorFlow?** The learning curve is a bit steep.The tutorials on the website can be more explicitly explained. **Recommendations to others considering TensorFlow:** Get yore basics of python,numpy and ML strong before using TensorFlow **What problems is TensorFlow solving and how is that benefiting you?** I use tensor flow to solve complex classification problems especially delaying with Images,as Image processing and machine/deep learning go hand in hand for classification problems ### 34. Simple, Fast and easy **Rating:** 3.5/5.0 stars **Reviewed by:** Naveen K. | Mid-Market (51-1000 emp.) **Reviewed Date:** February 02, 2018 **What do you like best about TensorFlow?** Efficiency and the ease of deployment during projects **What do you dislike about TensorFlow?** Boot up time and the sometimes the clumsiness **What problems is TensorFlow solving and how is that benefiting you?** Data Management ### 35. TensorFlow with Keras over Spark is a great solution **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** March 20, 2018 **What do you like best about TensorFlow?** Easy of creating models and parameterizing them **What do you dislike about TensorFlow?** Need experienced programmers to set it up and train the models **Recommendations to others considering TensorFlow:** Include Keras to further automate **What problems is TensorFlow solving and how is that benefiting you?** Predictive Analytics Resource optimization ### 36. Best deep learning software **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Hospital & Health Care | Small-Business (50 or fewer emp.) **Reviewed Date:** January 31, 2018 **What do you like best about TensorFlow?** Good documentation, large support community **What do you dislike about TensorFlow?** learning curve with backgrounds like Java, DotNet and Javascript etc **Recommendations to others considering TensorFlow:** Ability to build models and train them easily with Tensorflow. Best tool for data scientists **What problems is TensorFlow solving and how is that benefiting you?** Deep learning models to predict certain outcomes ### 37. A very great tool for engineers to work on Deep Learning. **Rating:** 4.0/5.0 stars **Reviewed by:** Da T. | Technology Consultant, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** February 08, 2017 **What do you like best about TensorFlow?** There is a very great ecosystem around TensorFlow, such as TensorBoard for visualizing computation graph, TensorFlow Serving for manage model in production, TFSlim for simplification of building neural network, and so on. TensorFlow is also evolving very fast and it is nearly going to get 1.0 release. **What do you dislike about TensorFlow?** It is a little hard for new comer to learn. The API is not that friendly for non-research background people. **Recommendations to others considering TensorFlow:** People who want to use TensorFlow should have enough machine learning background, especially deep learning. To use it in a GPU cluster is not that easy. Learning to use its API also cost a lot of time. But to my extent, TensorFlow is really the best in engineering support among all the deep learning framework. Moreover, people could use Keras on TensorFlow to build network more easily. **What problems is TensorFlow solving and how is that benefiting you?** We use it to solve computer vision problem as a proof of concept. It worked fine. ### 38. Amazing **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Education Management | Enterprise (> 1000 emp.) **Reviewed Date:** October 24, 2017 **What do you like best about TensorFlow?** The easy environment to adapt. Working online community is awesome... Thank you guys **What do you dislike about TensorFlow?** Some dependencies are that easy to work with, RNNs are still a bit lacking, compared to Theano. **Recommendations to others considering TensorFlow:** Theano **What problems is TensorFlow solving and how is that benefiting you?** designing a hardware to help the blind peoples recognize there loved ones ## TensorFlow Discussions - [What is TensorFlow and why it is used?](https://www.g2.com/discussions/what-is-tensorflow-and-why-it-is-used) - 2 comments - [View TensorFlow pricing details and edition comparison](https://www.g2.com/products/tensorflow/reviews?page=3§ion=pricing&secure%5Bexpires_at%5D=2026-05-25+23%3A30%3A01+-0500&secure%5Bsession_id%5D=1b666c64-1547-49dc-9074-695178382c78&secure%5Btoken%5D=d1fc4d9cc6e9c853c8e47ffbb823a25af20d98a08110d7a7f9a545990c434d7a&format=llm_user) ## TensorFlow Integrations - [AWS Lambda](https://www.g2.com/products/aws-lambda/reviews) - [Keras](https://www.g2.com/products/keras/reviews) - [KeTengo](https://www.g2.com/products/ketengo/reviews) - [Python](https://www.g2.com/products/python/reviews) - [SpotOn](https://www.g2.com/products/spoton/reviews) ## TensorFlow Features **System** - Data Ingestion & Wrangling **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training **Model Development** - Feature Engineering **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Deployment** - Managed Service - Application - Scalability **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making ## Top TensorFlow Alternatives - [MATLAB](https://www.g2.com/products/matlab/reviews) - 4.5/5.0 (749 reviews) - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (650 reviews) - [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews) - 4.2/5.0 (161 reviews)