10 Common Mistakes in Data Science Projects and How to Avoid Them

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10 Common Mistakes in Data Science Projects and How to Avoid Them

This blog post was originally published at Digica’s website. It is reprinted here with the permission of Digica. While Data Science is an established and highly esteemed profession with strong foundations in science, it is important to remember that it is still a craft and, as such, it is susceptible to errors coming from processes that may be not suited to the problem at hand, the amount of data made available by the customer or industry standa…