Leaf vs Pipelines: What are the differences?
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; Pipelines: Machine Learning Pipelines for Kubeflow. Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. Kubeflow pipelines are reusable end-to-end ML workflows built using the Kubeflow Pipelines SDK.
Leaf and Pipelines belong to "Machine Learning Tools" category of the tech stack.
Leaf and Pipelines are both open source tools. Leaf with 5.4K GitHub stars and 270 forks on GitHub appears to be more popular than Pipelines with 944 GitHub stars and 247 GitHub forks.