Keras vs Tensor2Tensor: What are the differences?
What is Keras? Deep Learning library for Theano and TensorFlow. Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/.
What is Tensor2Tensor? Library of deep learning models & datasets designed to make deep learning more accessible (by Google Brain). It is a library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. It was developed by researchers and engineers in the Google Brain team and a community of users.
Keras and Tensor2Tensor can be categorized as "Machine Learning" tools.
Some of the features offered by Keras are:
- neural networks API
- Allows for easy and fast prototyping
- Convolutional networks support
On the other hand, Tensor2Tensor provides the following key features:
- Many state of the art and baseline models are built-in and new models can be added easily
- Many datasets across modalities - text, audio, image - available for generation and use, and new ones can be added easily
- Models can be used with any dataset and input mode (or even multiple)
Keras and Tensor2Tensor are both open source tools. Keras with 47.2K GitHub stars and 17.9K forks on GitHub appears to be more popular than Tensor2Tensor with 9.7K GitHub stars and 2.51K GitHub forks.
