As work on a data science project starts, you write code to get acquainted with the data, test hypotheses and train a baseline model. At some point, this code needs to be organized in a way that allows experimentation and collaboration on project code. In this case, the BatchFlow library can come to the rescue to conveniently structure the code and implement data processing as pipelines.

BatchFlow is an open-source Python framework to deal with data handling, ML model training and all related things. One can use the library for constructing very clear and expressive pipelines that describe:

  • data loading…

Alexey Kozhevin

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