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Use packages which include dplyr to wrangle and clean up the datasets. Then use ggplot2 to generate some facts visualizations of temperature and climate developments.
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Then use logistic regression to coach a product about the dataset and make churn predictions on unseen purchaser knowledge. You may as well examine other machine learning strategies for example decision trees or random forests if it applies.
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Bayesian studies utilize the mathematical language of likelihood to describe epistemological uncertainty. With this, the chance expresses the degree of belief that may be laid out in the states of nature.