Learn to perform linear and logistic regression with multiple explanatory variables.
Linear regression and logistic regression are the two most widely used statistical models and act like master keys, unlocking the secrets hidden in datasets. Through hands-on exercises, you’ll explore the relationships between variables in real-world datasets, Taiwan house prices and customer churn modeling, and more. By the end of this course, you’ll know how to include multiple explanatory variables in a model, understand how interactions between variables affect predictions, and understand how linear and logistic regression work.阅读更多.
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The techniques and tools covered in Intermediate Regression in R are most similar to the requirements found in 数据科学家 data science job advertisements.
