¿What Is A Data Science Tournament?

Data science, as opposed to web or mobile development, has a relatively easy way to measure the outcome: through evaluation metrics. In software development the outcome expected by stakeholders is given by a number of subjective things, such as user onboarding, UX/UI or security.

This evaluation is not specifically measured by some objective and unique metric. In data science the opposite happens, because we have the evaluation metrics, that we can choose a metric for a given problem, making a model easily evaluable, since we will always have an objective value as a result of the quality. The problem is to choose the right metric, and that would already be a different problem.

Those evaluation metrics leave the doors open for us to easily measure the skills of data scientists, and to evaluate the effectiveness of their models. That is why data science tournaments have been born.

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