AutoMLPipeline vs Keras: What are the differences?
What is AutoMLPipeline? A package that makes it trivial to create and evaluate machine learning pipeline architectures (by IBM). It is a package that makes it trivial to create complex ML pipeline structures using simple expressions. It leverages on the built-in macro programming features of Julia to symbolically process, manipulate pipeline expressions, and automatically discover optimal structures for machine learning prediction and classification.
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/.
AutoMLPipeline and Keras can be primarily classified as "Machine Learning" tools.
Some of the features offered by AutoMLPipeline are:
- Pipeline API that allows high-level description of processing workflow
- Common API wrappers for ML libs including Scikitlearn, DecisionTree, etc
- Symbolic pipeline parsing for easy expression of complexed pipeline structures
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 47K GitHub stars and 17.8K GitHub forks. Here's a link to Keras's open source repository on GitHub.
