Technical Debt in software development is pervasive. With machine learning engineering maturing, this classic trouble is unsurprisingly rearing its ugly head. These 25 best practices, first described in 2015 and promptly overshadowed by shiny new ML techniques, are updated for 2020 and ready for you to follow — and lead the way to better ML code and processes in your organization.
Originally from KDnuggets https://ift.tt/2YbBWhH
source https://365datascience.weebly.com/the-best-data-science-blog-2020/nitpicking-machine-learning-technical-debt
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