# 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, enabling complex ML projects with ease and efficiency. (23 reviews) - Users love the **flexibility and powerful features** of TensorFlow, enhancing their AI integration experience across diverse applications. (19 reviews) - Users find TensorFlow's **ease of use** and robust community support invaluable for building and training models effectively. (19 reviews) - Users appreciate the **model variety** in TensorFlow, enabling diverse projects across various hardware and platforms. (18 reviews) - Users value 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 find the **steep learning curve** of TensorFlow challenging, requiring significant time and effort to master. (25 reviews) - Users find TensorFlow's **complexity** challenging, especially for beginners dealing with model conversion and debugging. (8 reviews) - Users find the **difficult learning curve** of TensorFlow challenging, making it hard for beginners to master. (8 reviews) - Users find **error handling frustrating** , with complicated messages and poor stack traces hinder debugging efforts greatly. (6 reviews) - Users often face **slow performance** with TensorFlow, especially when executing complex models, which can be frustrating. (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. Best Suited for the Machine learning tasks **Rating:** 5.0/5.0 stars **Reviewed by:** Bindiya S. | Research Software engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** More modular approach than Pytorch and keras layers makes model making a lot easier **What do you dislike about TensorFlow?** Tensorflow has no such downsides but compared to pytorch a bit slower **What problems is TensorFlow solving and how is that benefiting you?** Machine learning models, especially the time series forecasting using LSTM and the convolution neural networks for image prediction. ### 2. Tensorflow review **Rating:** 5.0/5.0 stars **Reviewed by:** Mohidhar Y. | Technology Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** TensorFlow is widely appreciated for its versatility in handling diverse machine learning tasks and seamless deployment across platforms. Its rich ecosystem, including TensorFlow Lite and TFX, makes it ideal for both research and production. **What do you dislike about TensorFlow?** ensorFlow is a powerful tool, some users find its steep learning curve and verbose syntax challenging, especially for beginners. **What problems is TensorFlow solving and how is that benefiting you?** It tackles a variety of challenges in machine learning, such as simplifying the creation of complex neural networks, facilitating model scalability, and optimizing performance with hardware acceleration. ### 3. Great Deep Learning Framework **Rating:** 4.5/5.0 stars **Reviewed by:** haibing l. | director, Small-Business (50 or fewer emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** Highly flexible and scalable Excellent support for building complex neural networks Strong ecosystem Active community and extensive documentation **What do you dislike about TensorFlow?** Steeper learning curve for beginners Debugging an be challenging **What problems is TensorFlow solving and how is that benefiting you?** TensorFlow streamlines the end-to-end machine learning workflow. Greatly accelerated my development time ### 4. AI and Machine Learning **Rating:** 4.5/5.0 stars **Reviewed by:** Amit k. | Senior Business Development Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** April 03, 2025 **What do you like best about TensorFlow?** Ease of Use, they've got fantastic customer support. The number of features are far better than other open source software's available in the market. Ease of integration across various platforms and can easily implement by using frequently. **What do you dislike about TensorFlow?** Less flexibility in static computation graph. No support for windows **What problems is TensorFlow solving and how is that benefiting you?** It has excellent community support, it is ideal for large projects, addresses deep learning or machine learning issues such as creation, discovery, classification, understanding and prediction. ### 5. Best solution for Deep Learning **Rating:** 4.5/5.0 stars **Reviewed by:** Manash Kumar M. | Doctoral Researcher, Education Management, Small-Business (50 or fewer emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** Ability to execute low-level operations across many accelerations platforms. Easy to use , easily integration **What do you dislike about TensorFlow?** Slower competition speed, limited support **What problems is TensorFlow solving and how is that benefiting you?** I am a research scholar of Computer Science. I general use deep learning projects using TenserFlow ### 6. It was quite better **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Human Resources | Mid-Market (51-1000 emp.) **Reviewed Date:** July 25, 2025 **What do you like best about TensorFlow?** It was good for Production-ready ML systems, large-scale model training, and cross-platform deployment **What do you dislike about TensorFlow?** Steeper learning curve compared to PyTorch for beginners Verbose syntax in low-level APIs Debugging can be complex in dynamic environments **What problems is TensorFlow solving and how is that benefiting you?** TensorFlow solves the problem of building, training, and deploying machine learning (ML) and deep learning (DL) models at scale. ### 7. "TensorFlow: Power, Flexibility, and Real-World Usability" **Rating:** 3.0/5.0 stars **Reviewed by:** Trashi S. | Integration Engineer (MySQL DBA), Enterprise (> 1000 emp.) **Reviewed Date:** April 02, 2025 **What do you like best about TensorFlow?** It’s great for training AI models efficiently, especially on large datasets. You can use it on mobile, web, or even in big production systems. **What do you dislike about TensorFlow?** It can be tricky for beginners compared to some other AI tools. Writing TensorFlow code can be more complex compared to other frameworks like PyTorch. **What problems is TensorFlow solving and how is that benefiting you?** TensorFlow helps predict slow queries and recommends indexing or query optimizations. Predicts future database growth based on past usage trends. ### 8. TensorFlow for Machine Learning **Rating:** 5.0/5.0 stars **Reviewed by:** Alkaid P. | Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** I how tensorflow has a high quality in terms of training **What do you dislike about TensorFlow?** Sometimes it require a huge amount of mb for a model **What problems is TensorFlow solving and how is that benefiting you?** Automating applications by using a machine learning model ### 9. Powerful and Scalable Deep Learning Framework Backed by Google **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Small-Business (50 or fewer emp.) **Reviewed Date:** April 08, 2025 **What do you like best about TensorFlow?** TensorFlow offers incredible flexibility and scalability for building machine learning and deep learning models. I particularly appreciate the tight integration with Keras, which makes it easy to prototype models quickly. TensorBoard is also a great tool for visualizing training metrics. **What do you dislike about TensorFlow?** The learning curve can be steep for beginners, especially when working with low-level APIs or custom training loops. Also, compared to PyTorch, the syntax can feel more verbose and less intuitive at times. **What problems is TensorFlow solving and how is that benefiting you?** I use TensorFlow to build and deploy deep learning models for classification, object detection, and time-series forecasting. During my finals ### 10. Powerful and Flexible tool **Rating:** 5.0/5.0 stars **Reviewed by:** Siddharth N. | Data Associate & Project Management, Small-Business (50 or fewer emp.) **Reviewed Date:** September 14, 2024 **What do you like best about TensorFlow?** I love how flexible TensorFlow is. Whether I’m working on a small project or something more advanced, TensorFlow gives me the tools I need to build and fine-tune my models. The pre-trained models and built-in support for both mobile and cloud deployment are also a huge time-saver, letting me get up and running quickly. **What do you dislike about TensorFlow?** I find that TensorFlow can be a bit overwhelming at first, especially for beginners like me. Some of the advanced features, like creating custom layers or debugging complex models, took a while to understand. It also seems to run slower than other frameworks when I’m training larger models. **What problems is TensorFlow solving and how is that benefiting you?** I use TensorFlow primarily for building and deploying machine learning models. It helps me solve complex problems like image recognition, natural language processing, and predictive analysis efficiently. TensorFlow's ability to handle large datasets and perform automatic optimization is a huge benefit, as it saves me time while ensuring the accuracy of my models. Additionally, its strong community support and wide range of tools and resources have been invaluable in streamlining my data science projects. ### 11. A good platform to learn machine Learning **Rating:** 4.0/5.0 stars **Reviewed by:** pankaj v. | Software Engineer II, Small-Business (50 or fewer emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** Good API and great code samples which helps to easy integrate. **What do you dislike about TensorFlow?** Need more resources around, if we are stuck there are less resources to help. Otherwise we have to go through documentation to understand **What problems is TensorFlow solving and how is that benefiting you?** I am using it to mode data filtering ### 12. Great experience **Rating:** 4.5/5.0 stars **Reviewed by:** Daniel C. | Consultant, Mid-Market (51-1000 emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** its a framework easy to use, implement, understand and debug **What do you dislike about TensorFlow?** In some cases its difficult to integrate with functionalities outside of the framework **What problems is TensorFlow solving and how is that benefiting you?** Create solutions trougth all the lifecycle of a machine learning model ### 13. Powerful & Scalable AI Framework **Rating:** 5.0/5.0 stars **Reviewed by:** Shobit S. | data manger, Banking, Small-Business (50 or fewer emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** I like Strong Ecosystem and Community and also Integration with Keras **What do you dislike about TensorFlow?** Less Intuitive than PyTorch and Difficult Debugging due to static computation graphs **What problems is TensorFlow solving and how is that benefiting you?** Tensorflow provided Faster Development and improving productivity. ### 14. Description of Tensor flow **Rating:** 5.0/5.0 stars **Reviewed by:** Enmanuel M. | Assistant Research Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** April 03, 2025 **What do you like best about TensorFlow?** The versatility and the scalability of TensorFlow. **What do you dislike about TensorFlow?** The complexity in the use of each one of the tools in addiction to the GPU limitations **What problems is TensorFlow solving and how is that benefiting you?** Speach recognition ### 15. A must have library for machine learning enthusiasts **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** April 03, 2025 **What do you like best about TensorFlow?** TensorFlow is easy to use, offers a rich documentation and has a huge community behind it that is always ready to help. **What do you dislike about TensorFlow?** When you grow out of the free tier the pricing can become a real headache like with other cloud tools. **What problems is TensorFlow solving and how is that benefiting you?** TensorFlow helps with building and testing models for deep learning. Helps with quick and easy iterating and bug fixing. ### 16. TensorFlow is great at data handling data well. **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Hardware | Mid-Market (51-1000 emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** TensorFlow supports a wide range of machine learning models. It works smoothly with different devices. I use this tool almost everyday. **What do you dislike about TensorFlow?** Few Control flow operations and loop functions are missing. **What problems is TensorFlow solving and how is that benefiting you?** It benefits greatly with respect to time. It produces results in reasonable time. Its flexibility over devices and machine learning models. its cost effective as well. ### 17. Neural Network with Keras- Tensor Flow **Rating:** 5.0/5.0 stars **Reviewed by:** Aanya S. | Project Manager, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** December 12, 2024 **What do you like best about TensorFlow?** Tensor Flow is easy to use, flexible with devices, runs machine directly in browser with java. **What do you dislike about TensorFlow?** Tool visualize can be more easy and pre trained models can done more frequently and can save more time. **What problems is TensorFlow solving and how is that benefiting you?** It solves scaliblity challenges and model development complexity. It benefits us through model building, end to end ML pipelines. ### 18. Solid and reliable framework for ML **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** April 01, 2025 **What do you like best about TensorFlow?** The scalability which allows for distributed training is great, and the API is very extensible. **What do you dislike about TensorFlow?** It does have a steep learning curve and it is very resource intensive. **What problems is TensorFlow solving and how is that benefiting you?** Building ML models to detect stop signs on the road and other objects ### 19. TensorFlow Review **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** April 02, 2025 **What do you like best about TensorFlow?** Capable of managing large datasets and supporting distributed computing. **What do you dislike about TensorFlow?** Needs more boilerplate code than PyTorch and other alternatives. **What problems is TensorFlow solving and how is that benefiting you?** Synthetic Data Generation for our Asset Management. Synthetic data augmentation techniques to train failure prediction models without real-world failure data. ### 20. Reviewing Tensorflow **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Education Management | Small-Business (50 or fewer emp.) **Reviewed Date:** April 06, 2024 **What do you like best about TensorFlow?** It's easy to integrate pre-trained models for building up the starter projects and tensorflow.js helped me out for integrating it directly into the browser. **What do you dislike about TensorFlow?** There were compatibility issues between different versions, to convert code from Tensorflow 1.0 to Tensorflow 2.0. Although change was good but it need now some changes to be made in order to make it compatible. **What problems is TensorFlow solving and how is that benefiting you?** I have used Tensorflow in building crop disease identification using lightweignt Convolutional Neural Network model. Building own Convolutional block seemed pretty easy using Tensorflow. ### 21. What an amazing library **Rating:** 5.0/5.0 stars **Reviewed by:** Gaurav . | AI Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** September 11, 2023 **What do you like best about TensorFlow?** The way it handles the data and the community support it has is a god sent. Developing and maintaining the code base is really easy with tensorflow. And with v2 it's just amazing. **What do you dislike about TensorFlow?** I think for a person just entering the industry it's somewhat difficult to understand. Sometimes the documentation is really confusing and you have to search if someone has explained it for you to understand it better. **What problems is TensorFlow solving and how is that benefiting you?** I am a machine learning engineer and hardly a day goes by when I don't have to use tensorflow because all our algorithms are written with tensorflow because of it's amazing community support. ### 22. Tensorflow the deep learning tool **Rating:** 4.5/5.0 stars **Reviewed by:** ARUNACHALAM K. | Engineer 1-Software, Enterprise (> 1000 emp.) **Reviewed Date:** October 13, 2023 **What do you like best about TensorFlow?** The libraries available in that library ,the convince it provides for creating Neural network model . **What do you dislike about TensorFlow?** No dislikes ,it's the best tool for Deep Learning **What problems is TensorFlow solving and how is that benefiting you?** By providing the essential tools and libraries for building or crafting deep learning models . ### 23. Train complex Machine learning model with ease by using tensorflow ! **Rating:** 4.5/5.0 stars **Reviewed by:** Yash R. | Full Stack Developer, Small-Business (50 or fewer emp.) **Reviewed Date:** February 20, 2023 **What do you like best about TensorFlow?** TensorFlow is flexible. It provides a platform for building and deploying machine learning models across a wide range of devices and media, and Tensorflow is really scalable, running on a single device to distributed systems with thousands of GPUs **What do you dislike about TensorFlow?** A few things I dislike about TensorFlow are it is resource intensive; TensorFlow is really resource intensive. It requires high computational power and a powerful GPU. the second thing is the learning curve TensorFlow can have a steep learning curve for beginners due to its complexity **What problems is TensorFlow solving and how is that benefiting you?** We were using TensorFlow to build a machine learning modal which can recognise potholes on roads using artificial intelligence and machine learning; we created it using python. ### 24. Tensorflow is the key to AI **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** June 05, 2023 **What do you like best about TensorFlow?** Tensorflow is the best library to work with neural networks and building model architecture. The functional API along with other functionalities makes it easy to define any model from easy to complex and train with ease. **What do you dislike about TensorFlow?** Tensorflow needs to add some development in context of memory. In order to deploy any model it takes around 400mb memory for just tensorflow lib. This is the only part which holds me back sometimes. **What problems is TensorFlow solving and how is that benefiting you?** It allows us to build model architecture in AI from easy to complex with simplicity. It really helps to perform EDA through the TFX library and build AI models with minimal code. ### 25. A solid framework for deep neural networks **Rating:** 4.0/5.0 stars **Reviewed by:** Shraval V. | ISA, Mid-Market (51-1000 emp.) **Reviewed Date:** December 07, 2022 **What do you like best about TensorFlow?** One of the best features of Tensorflow is its ability to perform multicore training of models. Unlike the old frameworks, TF doesn't rely on single CPU training rather it allows distributed training of models which drastically decreases the training time we have several GBs of images to be trained for diffusion models. **What do you dislike about TensorFlow?** When developers are using Windows for development there are certain issues with the Python pip packages that are part of TF. There is no native support for Decision forests which is one of the most popular packages that is supported by other frameworks. I train la **What problems is TensorFlow solving and how is that benefiting you?** I train large amounts of data for classification and the old frameworks that run on single-core training consume several hours to just train a couple of GBs of images whereas when I train it on tensorflow it reduces the time by almost 50% with distributed training. ### 26. Worked with computer vision project using tensorflow **Rating:** 4.5/5.0 stars **Reviewed by:** Suvhradip G. | Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** April 13, 2023 **What do you like best about TensorFlow?** In tensorflow there have lots of methods for many purpose. And in tf you can do anything about deep learning. **What do you dislike about TensorFlow?** Tensorflow can build own UI for managing models and all. **What problems is TensorFlow solving and how is that benefiting you?** I am using tensorflow for training for deep neural nets for medical diseases detection and it quite perform well because I did lots of things by using tf thats why ### 27. Excellent Machine Learning Library **Rating:** 4.5/5.0 stars **Reviewed by:** Erick S. | Student, Small-Business (50 or fewer emp.) **Reviewed Date:** December 21, 2022 **What do you like best about TensorFlow?** Tensorflow has several intuitive methods for implementing machine learning algorithms. I personally like to use the image classification section to understand how to detect patterns in supervised data. **What do you dislike about TensorFlow?** I think there is still some room for improvement in terms of readability. In particular, it feels like many of TensorFlow's commands don't follow a "pythonic" pattern. **What problems is TensorFlow solving and how is that benefiting you?** Tensorflow is trying to make machine learning easier to implement for anybody who is just learning and understanding. Tensorflow is also allowing seasoned veterans to implement ML algorithms with ease. ### 28. a gpu based deep learning library by Google for python,c++ and java programmer. **Rating:** 4.5/5.0 stars **Reviewed by:** Abhuday T. | Assistant Professor, Small-Business (50 or fewer emp.) **Reviewed Date:** January 15, 2023 **What do you like best about TensorFlow?** It provides all the recent algorithms that can run on a Convolutional neural network model. It provides training algorithms, metrics and optimizers for the deep learning algorithm. **What do you dislike about TensorFlow?** Python version of TensorFlow runs only on GPU-based processors. **What problems is TensorFlow solving and how is that benefiting you?** It is a python, java and C++-based deep learning library that can help us solve data science and machine learning problems. ### 29. TensorFlow: Beginner friendly and Production Ready **Rating:** 5.0/5.0 stars **Reviewed by:** Navaneeth M. | Educator and Mentor, Small-Business (50 or fewer emp.) **Reviewed Date:** June 28, 2022 **What do you like best about TensorFlow?** Easy to get started with. The TensorFlow ecosystem provides support tools to load data efficiently (TF Dataloaders) , build models (Keras), Optimize it (TF Lite), and Deploy and monitor (TFX) and it is production-ready. **What do you dislike about TensorFlow?** One concern I have is inconsistent APIs and functions. Confusion with TF 1 and TF 2. Lots of duplicate and redundant methods. Code customization for research purposes. **What problems is TensorFlow solving and how is that benefiting you?** I am a Deep Learning Engineer and Educator. TF helps to build Neural Network models with less code using Keras API. Since Google is backing TensorFlow is robust for production level applications. ### 30. Easy to use and has a lot of inbuilt functionality and support for algorithms **Rating:** 5.0/5.0 stars **Reviewed by:** Sanket M. | Media Lead - CodeChef CGC Chapter, Small-Business (50 or fewer emp.) **Reviewed Date:** February 15, 2022 **What do you like best about TensorFlow?** Tensorflow is an excellent library for implementing linear algebra equations and algorithms. It also has Keras as its inbuilt module, a perfect module for deep learning and implementing neural network models. I use it majorly for implementing and training deep learning models. It provides high customizability for defining our loss functions, activation functions, etc. **What do you dislike about TensorFlow?** The Keras interface provided inside TensorFlow is not the same as externally importing Keras. There are a few differences which can someone comfortable with Keras make several mistakes while developing using Tensorflow. It also sometimes shows some errors which are easy to understand and often not even related to the code, but the running environment/kernel instead. **Recommendations to others considering TensorFlow:** If you are willing to get started with deep learning and deep neural networks, Tensorflow is one of the best options due to its applications, usability, and ease of use. **What problems is TensorFlow solving and how is that benefiting you?** Implementing deep neural networks is straightforward. Implementing non-linear neural networks also becomes more accessible through the functional interface provided by the module. The ability to implement custom algorithms to be used with neural networks also helps when writing research papers or implementing one. ### 31. Most mathematically-oriented ML framework **Rating:** 4.0/5.0 stars **Reviewed by:** Alex M. | Graduate Student Researcher, Enterprise (> 1000 emp.) **Reviewed Date:** November 30, 2021 **What do you like best about TensorFlow?** For people who grew up learning the math of backprop, who enjoy thinking about syntax trees and computation graphs, Tensorflow will allow you to make full use of you that insight. Interesting loss functions like Wasserstein loss (where the gradient itself enters as part of the loss function) enter naturally. **What do you dislike about TensorFlow?** The mix between Tensorflow v1 and v2 code is somewhat difficult to learn, if you only get into it now. Tensorflow v2 is modeled much more on Keras, and is designed for you to particular architectures and pipelines. That's great, but if you then want to mix that with the flexibility of v1, you run into a lot of pain. **What problems is TensorFlow solving and how is that benefiting you?** I've used Tensorflow as a black-box optimizer for searching for Quantum Error-Correcting Codes. That probably doesn't sound like Machine Learning, right? But it's gradient descent on large parallel datasets, so hey, it works. I've also seen it for e.g. physics simulations, card game simulation, a wide variety of "parallel" tasks. In the most liberal interpretation, Tensorflow is "CUDA but better": a way to use your GPU for parallel tasks in a general setting. ### 32. TensorFlow for Deep Learning problems and usecases, best one!!! **Rating:** 4.5/5.0 stars **Reviewed by:** poorna c. | Senior Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 05, 2022 **What do you like best about TensorFlow?** There are so many points which I liked aboutTensorFlow i.e. It is fast and it's scalability on the larger dataset, Witht the help of TensorFlow I am able to write customisable evaluation functions. **What do you dislike about TensorFlow?** Overall performance of TensorFlow is good but the documentation of TensorFlow can be improved, Sometime i felt inconsistency in the algorithm which can be further optimised. **What problems is TensorFlow solving and how is that benefiting you?** With the help of TensorFlow I have implemented and solved multiple problems of Deep learning. I have implemented deep neural networks for solving the problems in the medical domain. ### 33. Like why would you use another ML platform **Rating:** 5.0/5.0 stars **Reviewed by:** Kushal P. | Software Engineer II, Small-Business (50 or fewer emp.) **Reviewed Date:** December 21, 2021 **What do you like best about TensorFlow?** Python based and API is intuitive. Keras is great and uses the Tensorflow library. I used scikit-learn prior and it was so much harder to understand and require way more code to get the same things done. The user-friendly interface is honestly the best part of Tensorflow/Keras. **What do you dislike about TensorFlow?** Not a lot, but for Tensorflow Lite, a user manual to port to other boards would be great. I wanted to use Tensorflow Lite on my TM4C123GXL board, but it's not a supported platform. I am sure there is a way to get it running on any board, I just do not know how. **Recommendations to others considering TensorFlow:** Look no further, this is the ML platform to use. **What problems is TensorFlow solving and how is that benefiting you?** Mainly educational purposes. I wanted to create a fire detection program that I hoped could be used to combat wildfires. I haven't really gotten the time to do this, but I still want to do it. ### 34. Best Platform for Building Deep learning models and Train them **Rating:** 5.0/5.0 stars **Reviewed by:** Doolitha S. | Software Engineer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** September 30, 2021 **What do you like best about TensorFlow?** It was easy to get on with Tensorflow compared to other machine learning libraries. There are tons of community support, tutorials, videos, and even pre-build models to learn and get maximum out of it in a short time. And what's more, it's completely free and open-source. **What do you dislike about TensorFlow?** There is nothing to say in this section. Tensorflow has it all, and I love it. I haven't faced a serious issue yet, and even If I did, the community is there to solve them happily. **Recommendations to others considering TensorFlow:** It's a must-use library for anyone who is into deep learning and model creation and training. **What problems is TensorFlow solving and how is that benefiting you?** I used Tensorflow for part of my final year research project. It was fun to learn and train the model as for my requirement. In the end, I was able to implement it without issues, and it was a success. I realized the true potential of Tensorflow. ### 35. Framework for solving Machine Learning Problem **Rating:** 4.5/5.0 stars **Reviewed by:** Chandresh M. | System Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** September 21, 2021 **What do you like best about TensorFlow?** The main important thing I like about Tensorflow is, it is Open Source. Anyone can use it and can create multiple Machine Learning applications. I can also visualize my machine learning model in TensorFlow by using Tensorboard. Tensorflow also supports Keras, so we can easily create ML and CNN models using it. Tensorflow is compatible with many programming languages like Java, Python, C++, Ruby etc. **What do you dislike about TensorFlow?** One thing I don't like about Tensorflow is, it gives updates regularly. So it becomes a little bit difficult to install new versions. Because sometimes, whatever application I developed may not be supported on a more recent version of Tensorflow. **Recommendations to others considering TensorFlow:** I recommend to the ones who want to develop applications quickly and beginner-friendly. **What problems is TensorFlow solving and how is that benefiting you?** I am using Tensorflow for creating Machine Learning and Deep Learning Applications. ### 36. Great framework for production grade model development and deployment **Rating:** 4.5/5.0 stars **Reviewed by:** Kevin P. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** August 10, 2021 **What do you like best about TensorFlow?** Tensorflow is a mature framework that offers many valuable features such as Keras, Tensorboard, data processing modules, easy-to-implement multiprocessing, integration with HDFS, and more. Tensorflow has a strong community and very robust documentation. Tensorflow has many time-saving features, such as easily integrated pre-trained model layers. The TensorFlow model hub is one of the best I have seen in terms of ease of finding and using pre-trained models. There are many demos and example notebooks that demonstrate how to use complex and straightforward concepts. **What do you dislike about TensorFlow?** Tensorflow has gone through many iterations over the past years, so code maintenance has been an issue. In my opinion, eager execution is a preferred method of developing and debugging networks; however, experience with legacy TensorFlow makes the switch more challenging. Since the deep learning research community favors PyTorch over TensorFlow, researchers generally find state-of-art models and new methodologies implemented in PyTorch. **Recommendations to others considering TensorFlow:** Start by looking at examples provided by the developers. Use TensorBoard **What problems is TensorFlow solving and how is that benefiting you?** We have developed custom models using the Keras API. We have used pre-trained (EfficientNet) models to solve various batch and real-time modeling needs in tabular and image processing learning paradigms. We are also looking into the TensorFlow decision forest package to keep all model development consistent. We use TensorFlow as both an experimental as well as a real-time production platform. ### 37. TensorFlow for AI Model Development **Rating:** 5.0/5.0 stars **Reviewed by:** KanuPriya K. | Product Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** November 10, 2021 **What do you like best about TensorFlow?** The most valuable part of TensorFlow is the Tensorboard. While training the AI model development, it provides better visualization for debugging and error handling. **What do you dislike about TensorFlow?** The least liked part of TensorFlow is it's implementation speed. In comparison to another deep learning framework, development time is higher in TensorFlow **What problems is TensorFlow solving and how is that benefiting you?** I am using TensorFlow Framework for complex Neural Network Implementations and Face Recognition deep learning model development. ### 38. Tensorflow review **Rating:** 4.5/5.0 stars **Reviewed by:** Hiteshi Jain . | Senior Applied Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** December 23, 2021 **What do you like best about TensorFlow?** Tensorflow is very mature deep learning library which is heavily used in production scenarios. I particularly like the tensorflow-lite version which comes along which reduces the size of the model and is good to deploy in edge devices. **What do you dislike about TensorFlow?** It requires a little more coding as compared to pytorch. Pytorch is more pythonic and hence is easier to learn and implement **What problems is TensorFlow solving and how is that benefiting you?** For deep learning model development for the industry I am working in ### 39. Graphical computation in deep learning **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** November 25, 2021 **What do you like best about TensorFlow?** The fact is that you can create the network and then do computation all at once. The computation is well optimized to run on GPU. The tensorboard support enables us to view the metric like accuracy and weights during the training which is absent in other deep learning packages **What do you dislike about TensorFlow?** The high level api is not present in the package itself. For that we need to use keras or other packages which is build on top of this but these high level API is not native to tensorflow **What problems is TensorFlow solving and how is that benefiting you?** Building and training deep neural networks. Getting deep into the training process and visualizing it does makes a lot of difference in getting very accurate models. ### 40. Perfect for neural networks **Rating:** 4.5/5.0 stars **Reviewed by:** deniz y. | Business Intelligence Manager, Enterprise (> 1000 emp.) **Reviewed Date:** September 21, 2021 **What do you like best about TensorFlow?** It works wonders when processing image, text and audio data. The documentation is very good and easy to use. With Keras, you can do your deep learning work simply and quickly. Open source. The best software library on the market for deep learning. It's reassuring to have Google behind it. Documentation is being updated. Functional. **What do you dislike about TensorFlow?** It's forcing the video card. Detecting and resolving errors is sometimes difficult. **What problems is TensorFlow solving and how is that benefiting you?** I can easily process my data with the models I have prepared. ### 41. Tensorflow ML platform **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Semiconductors | Mid-Market (51-1000 emp.) **Reviewed Date:** December 01, 2021 **What do you like best about TensorFlow?** Very powerful platform with Keras and other ml/dl libraries TFRecord is very efficient way of handling/storing data **What do you dislike about TensorFlow?** Very heavy software for inferencing though TFLite is good for mobile **What problems is TensorFlow solving and how is that benefiting you?** Training ML models for computer vision, natural language processing and graph neural networks. ### 42. Framework with ease access of AI ML APIs **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** September 27, 2021 **What do you like best about TensorFlow?** Graph visualisation in tensorflow is much better. Frequent updates as its backed by Google. **What do you dislike about TensorFlow?** Tensorflow lacks behind in terms of computation and speed. It's only supported in NVIDIA GPUs. **What problems is TensorFlow solving and how is that benefiting you?** Tensorflow helps us to train and deploy deep learning based model with ease. ### 43. Awesome framework for use of image processing solutions **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** September 22, 2021 **What do you like best about TensorFlow?** Easy to train images and create models which you can use in multiple plateforms like Windows, embedded devices and Mobile applications. **What do you dislike about TensorFlow?** Sometime it is hang on medium config system otherwise it is ok. **What problems is TensorFlow solving and how is that benefiting you?** Trains and use model for image processing solutions. ### 44. Best for Neural Network Modelling and Other ML Project **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Wireless | Mid-Market (51-1000 emp.) **Reviewed Date:** September 20, 2021 **What do you like best about TensorFlow?** This is having will defined and organized Classes for NN **What do you dislike about TensorFlow?** Sometimes dependencies give error during run time **What problems is TensorFlow solving and how is that benefiting you?** I am doing a project that is based on Deep NN and Reinforcement learning ### 45. Best way to jump start ML development **Rating:** 4.5/5.0 stars **Reviewed by:** Aravind S. | Research Scholar, Small-Business (50 or fewer emp.) **Reviewed Date:** August 07, 2020 **What do you like best about TensorFlow?** The Keras interface is super cool for beginners. Once you get comfortable, there are ample option to customize the data access during training and export the model. **What do you dislike about TensorFlow?** Its lerning curve is a little steep once you cross the beginners threshold. But can say its the worst :). **What problems is TensorFlow solving and how is that benefiting you?** I worked on using ML in solving classification of signal events from background events in data from Particle Physics experiments. I was able to make a new classifier that had 90%+ purity compared to the existing benchmark of 70%. The model deployment was also pretty quick with GPU back-end available. I am now working on porting things to FPGA based accelerator and the framework I am using supports TF too.. The wide documentation and user support forums are plus points too. ### 46. Essential Toolkit for Machine Learning and Deep Learning Research and Development Projects **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.) **Reviewed Date:** August 07, 2020 **What do you like best about TensorFlow?** Useful in all stages of development and production as well as most types of research work. It also gathers extensive pre-built and pre-trained systems and allows high level and low level access to most if not all components of the model. **What do you dislike about TensorFlow?** The team behind tensorflow is doing a great job and there is very little to dislike about it. Of course like every library, first comers will take a bit of time to get acquainted to it but it is getting easier to use with every version update.For new comers, watch out of the big shifts between some versions, which might require a bit of more work for compatibility. **Recommendations to others considering TensorFlow:** 1-Usually the team takes care of compatibility problems but the users must be aware that they exist. 2-Conda's installation facilitate the installation of dependency libraries such as CUDA for the GPU version. **What problems is TensorFlow solving and how is that benefiting you?** I am solving research problems and production level applications in the domain of human-agent interactions (using several different modalities of the human expressions: speech, vision and motion capture mainly). Tensorflow facilitates both quick prototyping and implementation of production level systems . ### 47. Using Deep Neurals Nets with a few lines of code **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Small-Business (50 or fewer emp.) **Reviewed Date:** August 11, 2020 **What do you like best about TensorFlow?** The Keras API: it makes building, training, working with DNNs, CNNs very easy. It requires only a very small knowlegde of (python) coding. Line by line one can add layers to the network to construct it, and the built-in optimizers do the training. No need to go through the pain if implementing backprop or optimizations steps on your own. Also nice: the support for GPUs which really speeds up all computions. **What do you dislike about TensorFlow?** The (remants of) older TF versions using weird and sometimes incomprehensible stuff like placeholder, logits, etc. **What problems is TensorFlow solving and how is that benefiting you?** As of now, used TF mainly as coding environent to actually learn ML, DNNs etc. The nice Keras API really helped me a lot to start my own ML exercise projects. ### 48. Neural network at your hands **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Chemicals | Mid-Market (51-1000 emp.) **Reviewed Date:** August 08, 2020 **What do you like best about TensorFlow?** Neural network application has become so easy. User now no need to focus on the development and optimising the models, and rather could stay more focused with the application part of it. **What do you dislike about TensorFlow?** Required Memory and ram size could be optimized. **Recommendations to others considering TensorFlow:** Using tensor flow the user gets the space to focus more towards the application perspective rather than spending time on its development. **What problems is TensorFlow solving and how is that benefiting you?** Manufacturing requirements lated challenges. Modeling the frameworks using tensor flow is now easy and handy. ### 49. I used TensorFlow for my some of course projects **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** September 01, 2020 **What do you like best about TensorFlow?** It is open-source and can use for different platforms. There are lots of tutorials available that can make help students when that stuck in some part. Also, I really like the visualization tools of that through TensorBoar. **What do you dislike about TensorFlow?** I have a windows machine and there is no support for Windows **Recommendations to others considering TensorFlow:** The best way to use it is through python because there are lots of tutorials for that. Also, using Keras through TensorFlow is also fabulous **What problems is TensorFlow solving and how is that benefiting you?** I used for my text analysis class and machine learning class to solve the class project on time series and CNN ### 50. Make Neural Networks Recognize Objects and Images **Rating:** 4.5/5.0 stars **Reviewed by:** Vincenzo C. | Gerente de operaciones, Internet, Mid-Market (51-1000 emp.) **Reviewed Date:** October 01, 2019 ## 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=2§ion=pricing&secure%5Bexpires_at%5D=2026-05-14+06%3A09%3A06+-0500&secure%5Bsession_id%5D=7c7473b4-c34d-4f6e-90c5-be9d97a1b689&secure%5Btoken%5D=49b7b099b6d912382f54e3c1aed1a95da31038e1e289230dcaee6e75ec777df7&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 (748 reviews) - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (647 reviews) - [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews) - 4.2/5.0 (160 reviews)