ScalaNLP vs baikal: What are the differences?

Developers describe ScalaNLP as "A suite of machine learning and numerical computing libraries". ScalaNLP is a suite of machine learning and numerical computing libraries. On the other hand, baikal is detailed as "A graph-based functional API for building complex scikit-learn pipelines". It is a graph-based, functional API for building complex machine learning pipelines of objects that implement the scikit-learn API. It is mostly inspired on the excellent Keras API for Deep Learning, and borrows a few concepts from the TensorFlow framework and the (perhaps lesser known) graphkit package. It aims to provide an API that allows to build complex, non-linear machine learning pipelines.

ScalaNLP and baikal belong to "Machine Learning Tools" category of the tech stack.

Some of the features offered by ScalaNLP are:

• ScalaNLP is the umbrella project for several libraries:
• Breeze is a set of libraries for machine learning and numerical computing
• Epic is a high-performance statistical parser and structured prediction library

On the other hand, baikal provides the following key features:

• Build non-linear pipelines effortlessly
• Handle multiple inputs and outputs
• Add steps that operate on targets as part of the pipeline

ScalaNLP and baikal are both open source tools. It seems that ScalaNLP with 3.07K GitHub stars and 682 forks on GitHub has more adoption than baikal with 553 GitHub stars and 23 GitHub forks.