The Power of Pipelines
Machine learning projects often require the execution of a sequence of data preprocessing steps followed by a learning algorithm. Managing these steps individually can be cumbersome and error-prone. This is where sklearn pipelines come into play. This post will explore how pipelines automate critical aspects of machine learning workflows, such as data preprocessing, feature engineering, and the incorporation of machine learning algorithms.
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The Power of Pipelines
Photo by Quinten de Graaf. Some rights reserved.
Overview
This post is divided into three parts; they are: