Machine Learning with Multiple Regression


In this first of a 3-part series, we will move from using regression as an exploratory tool to using it as a powerful machine learning technique. Using real-world case studies, we will see how to mine observational data from your processes and extract valuable information. We will learn how and when to use specific model validation methods, including validation with a test set, leave-one-out validation and k-fold cross validation. By incorporating validation into model assessment, you will discover how to improve the accuracy of your predictive models.

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