摘要: Learn about the standard process for building sustainable machine learning applications.


There are no standard practices for building and managing machine learning (ML) applications. As a result, machine learning projects are not well organized, lack reproducibility, and are prone to complete failure in the long run. We need a model that helps us maintain quality, sustainability, robustness, and cost management throughout the ML life cycle.

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▲圖片來源:kdnuggets

The Cross-Industry Standard Process for the development of Machine Learning applications with Quality assurance methodology (CRISP-ML(Q)) is an upgraded version of CRISP-DM to ensure quality ML products.

轉貼自: kdnuggets.com

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