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Data Science: Mindset, Methodologies, and Misconceptions by Zacharias Voulgaris PhD

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Chapter 9 Mistakes Through the Data Science Process

Mistakes are inevitable, not just in coding as we saw in the previous chapter, but also through the whole data science pipeline. This is more or less obvious. What is not obvious is that these mistakes are also learning opportunities for you, and that no matter how experienced you are, they are bound to creep up on you. Naturally, the better your grasp of data science, the lower your chances of making these mistakes, but as the field constantly changes, it is likely that you will not be on top of every aspect of it.

In this chapter, we will examine the difference between mistakes and bugs, the most common types of mistakes in data science, how the selection of a model can be erroneous (even ...

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