English | Size: 3.12 GB
Genre: eLearning
Learn
Understand the concept of regression
Build logistic regression models
Interpret regression results
Build linear regression models
Build count models
Visualize the results
About
Linear and logistic regressions are among the first set of algorithms you’ll study to get started on your journey in data science.
This course explores three basic regressions—linear, logistic, and count model. Starting with linear regressions, you’ll first understand the difference between simple and multiple linear regressions and explore different types of variables, including binary, categorical, and quadratic. Once you’ve got to grips with the fundamentals, you’ll apply what you’ve learned to solve a case study. As you advance, you’ll explore logistic regression models and cover variables, non-linearity tests, prediction, and model fit. Finally, you’ll get well-versed with count model regression.
By the end of the course, you’ll be equipped with the knowledge you need to investigate correlations between multiple variables using regression models.
All the codes and supporting files for this course will be available at-
https://github.com/PacktPublishing/Understanding-Regression-Techniques
Features
Understand the normality and independence of residuals
Explore both graphical and non-graphical tests for non-linearity in logistic regression models
Get to grips with count tables, their risk, and incidence rate ratio
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