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Then use logistic regression to practice a design on useful source the dataset and make churn predictions on unseen client details. You may also check out other equipment learning approaches for example conclusion trees or random forests if it applies.
Study the basic principles of combination functions in R with dplyr, which allow us to determine portions that describe groups of information.
Projects that may be finished with R include things like Checking out general public facts sets, generating an R shiny app, consumer segmentation working with clustering in R, weather and local climate alter forecasting, churn prediction working with logistic regression, text analytics projects, sentiment Examination projects, and World wide web scraping projects.