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PyBrain vs Keras: What are the differences?
PyBrain: A modular Machine Learning Library for Python. It's goal is to offer flexible, easy-to-use yet still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test and compare your algorithms; 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/.
PyBrain and Keras belong to "Machine Learning Tools" category of the tech stack.
Some of the features offered by PyBrain are:
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
On the other hand, Keras provides the following key features:
- neural networks API
- Allows for easy and fast prototyping
- Convolutional networks support
Keras is an open source tool with 49.7K GitHub stars and 18.6K GitHub forks. Here's a link to Keras's open source repository on GitHub.
Pros of Keras
- Quality Documentation8
- Supports Tensorflow and Theano backends7
- Easy and fast NN prototyping7
Pros of PyBrain
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Cons of Keras
- Hard to debug4
