What is baikal?
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.
baikal is a tool in the Machine Learning Tools category of a tech stack.
baikal is an open source tool with 579 GitHub stars and 29 GitHub forks. Here’s a link to baikal's open source repository on GitHub
Who uses baikal?
- Build non-linear pipelines effortlessly
- Handle multiple inputs and outputs
- Add steps that operate on targets as part of the pipeline
- Nest pipelines
- Use prediction probabilities (or any other kind of output) as inputs to other steps in the pipeline
- Query intermediate outputs, easing debugging
- Freeze steps that do not require fitting
- Define and add custom steps easily
- Plot pipelines
baikal Alternatives & Comparisons
What are some alternatives to baikal?
See all alternatives
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