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Go From Notebook To Pipeline For Your Data Science Projects With Orchest
Go From Notebook To Pipeline For Your Data Science Projects With Orchest
ratings:
Length:
44 minutes
Released:
Mar 2, 2021
Format:
Podcast episode
Description
Jupyter notebooks are a dominant tool for data scientists, but they lack a number of conveniences for building reusable and maintainable systems. For machine learning projects in particular there is a need for being able to pivot from exploring a particular dataset or problem to integrating that solution into a larger workflow. Rick Lamers and Yannick Perrenet were tired of struggling with one-off solutions when they created the Orchest platform. In this episode they explain how Orchest allows you to turn your notebooks into executable components that are integrated into a graph of execution for running end-to-end machine learning workflows.
Released:
Mar 2, 2021
Format:
Podcast episode
Titles in the series (100)
Ned Batchelder by The Python Podcast.__init__