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Bayes Rule in Python

In this exercise you will undertake a practical example of setting up Bayes formula, obtaining new evidence and updating your 'beliefs' in order to get a more accurate result. The example will relate to the likelihood that someone will close their account for your online software product.

These are the probabilities we know:

  • 7% (0.07) of people are likely to close their account next month
  • 15% (0.15) of people with accounts are unhappy with your product (you don't know who though!)
  • 35% (0.35) of people who are likely to close their account are unhappy with your product

This exercise is part of the course

Hyperparameter Tuning in Python

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Assign probabilities to variables 
p_unhappy = ____
p_unhappy_close = ____
Edit and Run Code