TensorFlow Reviews & Product Details

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.

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TensorFlow

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Value at a Glance

Averages based on real user reviews.

Time to Implement

3 months

Return on Investment

11 months

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Kushal P.

Software Engineer II

Small-Business (50 or fewer emp.)

12/21/2021

"Like why would you use another ML platform"

5/5

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Recommendations to others considering TensorFlow:

Look no further, this is the ML platform to use. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Doolitha S.

Software Engineer

Computer Software

Small-Business (50 or fewer emp.)

9/30/2021

"Best Platform for Building Deep learning models and Train them"

5/5

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Recommendations to others considering TensorFlow:

It's a must-use library for anyone who is into deep learning and model creation and training. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Chandresh M.

System Engineer

Mid-Market (51-1000 emp.)

9/21/2021

"Framework for solving Machine Learning Problem"

4.5/5

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Kevin P.

Data Scientist

Enterprise (> 1000 emp.)

8/10/2021

"Great framework for production grade model development and deployment"

4.5/5

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Recommendations to others considering TensorFlow:

Start by looking at examples provided by the developers.

Use TensorBoard Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

KanuPriya K.

Product Manager

Mid-Market (51-1000 emp.)

11/10/2021

"TensorFlow for AI Model Development"

5/5

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. Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

Hiteshi Jain .

Senior Applied Scientist

Small-Business (50 or fewer emp.)

12/23/2021

"Tensorflow review"

4.5/5

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. Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

Verified User in Information Technology and Services

Small-Business (50 or fewer emp.)

11/25/2021

"Graphical computation in deep learning"

4.5/5

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 Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

deniz y.

Business Intelligence Manager

Enterprise (> 1000 emp.)

9/21/2021

"Perfect for neural networks"

4.5/5

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. Review collected by and hosted on G2.com.

What do you dislike about TensorFlow?

It's forcing the video card. Detecting and resolving errors is sometimes difficult. Review collected by and hosted on G2.com.