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Data Science Blog

Machine learning & data science for beginners and experts alike.
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Community Content Engineer
Community Content Engineer

BIAS VS VARIANCE.png

There are two types of model errors when making an estimate; bias and variance. Understanding both of these types of errors, as well as how they relate to one another is fundamentally important to understanding model overfitting, underfitting, and complexity.

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Community Content Engineer
Community Content Engineer
Community Content Engineer
Community Content Engineer

ALL MODELS ARE WRONG.png

“Essentially, all models are wrong, but some models are useful.” Unpacking the famous George Box quote.

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Community Content Engineer
Community Content Engineer

 

SPECIFICATION GAMING1.png

Machines are not constrained by human experience or expectations, only by what we give them as inputs. This can be exciting and beautiful, or dangerous.

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