Building Reproducible Data Science Projects Using Pipelines and Version Control
Introduction In the era of data science, producing accurate results has become very important, but making those results reproducible is what a true professional is. Reproducibility simply refers to that anyone can repeat your project and come up with the same outcome without confusion. It covers transparency, reliability, and discipline, which you can also learn through a detailed course. For...
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