Summary

In this chapter, we talked about plotting and graphing your data and how to make your graphs look pretty using the matplotlib library in Python. We also walked through the concepts of covariance and correlation. We looked at some examples and figured out covariance and correlation using Python. We analyzed the concept of conditional probability and saw some examples to understand it better. Finally, we saw Bayes' theorem and its importance, especially in the medical field.

In the next chapter, we'll talk about predictive models.

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