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Leaf vs baikal: What are the differences?
What is Leaf? Machine learning framework in Rust. Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack.
What is baikal? 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.
Leaf and baikal can be categorized as "Machine Learning" tools.
Leaf and baikal are both open source tools. It seems that Leaf with 5.43K GitHub stars and 272 forks on GitHub has more adoption than baikal with 553 GitHub stars and 23 GitHub forks.
