3. Binary Classification


By the end of this chapter, you will be able to formulate a data science problem statement from a business perspective; build hypotheses from various business drivers influencing a use case and verify the hypotheses using exploratory data analysis; derive features based on intuitions that are derived from exploratory analysis through feature engineering; build binary classification models using a logistic regression function and analyze classification metrics and formulate action plans for the improvement of the model.

In this chapter, we will be using a real-world dataset and a supervised learning technique called classification to generate business outcomes.


In previous chapters, where an ...

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