Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Subscribe
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Tasting Machine Learning with Minitab Predictive Analytics
Rating: 4.8 out of 5(26 ratings)
1,940 students

Tasting Machine Learning with Minitab Predictive Analytics

Minitab Machine Learning Preview: A Bite-Sized Look at Predictive Analytics. Regression, Classification
Created byLászló Bognár
Last updated 3/2023
English

What you'll learn

  • Understand the concept of regression analysis and its applications in predictive modeling.
  • Understand the concepts of overfitting and underfitting.
  • Learn how to build a regression tree using Minitab.
  • Learn how to set up a binary logistic regression model using Minitab.
  • Practice building a classification tree and using it for prediction using Minitab.

Course content

1 section • 5 lectures • 58m total length

  • Regression 1. Setting up a Regression Model11:59

    This part of the analysis is to construct an easy- to-interpret regression model that highlights a possible function-like relationship between predictors and consumption.

  • Regression 2. Verification of the Model. Checking Over- or Underfitting12:07

    In the second phase of our data analysis, we will examine whether this model is overfitted. We use the Forward selection with validation version of the Stepwise Regression procedure.

  • Regression Tree14:44

    This example presents a predictive model using a regression tree to predict demand for bike sharing.

  • Classification with Binary Logistic Regression7:53

    In this lesson, we analyze a dataset of patients with heart failure.

  • Classification Tree11:34

    This example comes from the field of industrial applications, related to predictive maintenance of machines.

Requirements

  • No prior programming knowledge is required. The tutorials are based on Minitab software version 21. If you want to try it yourself on the data files provided, you will need this software. The 30-day trial is free. The course assumes basic statistical knowledge.

Description

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.

Who this course is for:

  • This course is for those who want a concise taste of the 4 basic methods of machine learning before embarking on a more detailed course.

Report abuse