Keras

Powerful open-source deep learning library for Python, providing easy-to-use tools for building neural networks, enabling developers to focus on model development.

Reviews and Ratings of Keras

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3.3 (201)

ROI

6%

Productivity

7%

Value for Money

4.7

Ease of Use

4.9

Support

3.4

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Keras Pricing Plans

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Free

For non-commercial use (personal projects)

Community

For open-source and free-use projects

Keras Product Reviews

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What verified reviews from expects say about
Keras

Insights from field experts about Keras from first hand.

T. Brooks

I've had an exceptional experience with Keras - its user-friendly interface and efficient deep learning capabilities have significantly streamlined my research projects, allowing me to focus on innovation and achieve outstanding results.

M. Robinson

I've had an incredibly smooth experience with Keras, effortlessly building and training complex neural networks in Python. The intuitive API and extensive community support have streamlined my workflow, making it a game-changer for deep learning projects.

C. Parker

Disappointing experience with Keras. Expected a seamless deep learning workflow but encountered numerous bugs and inconsistencies during model development and deployment. Lack of intuitive error handling and support for GPU acceleration made it a frustrating and time-consuming process.

P. Wilson

I've been thoroughly impressed with Keras' ease of use and flexibility in building deep learning models. Its intuitive API allowed me to quickly prototype and experiment with different architectures, while the modular design made it simple to customize and extend my projects. The comprehen...

C. Phillips

I'm thoroughly unimpressed with Keras. The steep learning curve, limited debugging tools, and frustratingly long run times made it a chore to use. Not impressed with the hype surrounding this library at all.

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Frequently asked questions about Keras

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What is Keras?

Keras is a high-level neural networks API, written in Python. It runs on top of TensorFlow, CNTK, or Theano.


Is Keras suitable for beginners?

Yes, Keras is considered one of the easiest deep learning frameworks to learn and use, making it a great choice for beginners.


What are the key features of Keras?

Keras' key features include its simplicity, flexibility, and ease of use. It also supports both convolutional neural networks (CNNs) and recurrent neural networks (RNNs).


Can I use Keras for production environments?

Yes, Keras can be used in production environments, especially when combined with a backend framework like TensorFlow. However, you may need to add additional features such as data parallelism and model serving.


What is the relationship between Keras and TensorFlow?

Keras runs on top of TensorFlow, which means that it uses TensorFlow's underlying infrastructure for computations, while providing a simpler and more intuitive API for users.



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