Tasting Machine Learning with Minitab Predictive Analytics

In this mini-course, “Tasting Machine Learning with Minitab Predictive Analytics”, you will gain an introduction to the world of predictive analytics and machine learning using Minitab statistical software.

Through five lectures, you will learn about regression analysis and classification, two fundamental techniques in predictive modeling. In the first two lectures, you will learn how to set up and verify regression models, as well as how to identify and address potential issues with overfitting or underfitting. In Lecture 3, you will explore regression trees, which are a powerful alternative to linear regression when the relationship between variables is non-linear.

In Lecture 4, you will delve into binary logistic regression, which is a technique used for predicting binary outcomes (such as “yes” or “no” responses). You will learn how to set up and evaluate a binary logistic regression model. Finally, in Lecture 5, you will discover classification trees, which are a type of decision tree used to classify objects or cases into different categories. You will learn how to build and interpret classification trees, and use them for prediction.

By the end of this mini-course, you will have gained practical experience in building and evaluating regression and classification models using Minitab, and an understanding of how these techniques can be applied in various real-world scenarios. Whether you are new to machine learning or looking to expand your knowledge, this mini-course is an excellent opportunity to explore the basics of predictive analytics with Minitab.