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Identifying features to convert

As Mark explained in the video, it is preferable to have features like 'Churn' encoded as 0 and 1 instead of no and yes, so that you can then feed it into machine learning algorithms that only accept numeric values.

Besides 'Churn', other features that are of type object can be converted into 0s and 1s. In this exercise, your job is to explore the different data types of telco in the IPython Shell and identify the ones that are of type object.

This exercise is part of the course

Marketing Analytics: Predicting Customer Churn in Python

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