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Data_hub

Uderstanding data science methods

Business understanding & problem framing: what is the context of this problem and why are they trying to solve it?

Exploratory data analysis & data cleaning: what data are we working with, what does it look like and how can we make it better?

Feature engineering: can we enrich this dataset using our own expertise or third party information?

Modeling and evaluation: can we use this dataset to accurately make predictions? If so, are they reliable?

Insights & Recommendations: how we can communicate the value of these predictions by explaining them in a way that matters to the business?

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