Linear and Logistic Regression

Overview

The linear and logistic regression course offers a detailed introduction to fundamental statistical and machine learning algorithms, particularly focusing on regression techniques. The course begins with simple linear regression and progresses to multiple linear regression, equipping students with the ability to analyze relationships between multiple variables. Finally, it covers logistic regression, a powerful tool for classification problems.

Syllabus

Introduction

In this lesson, we kick off the course with an introduction to machine learning and why linear regression is such an important algorithm.

Regression

In this lesson, you'll use Python to fit linear regression models, as well as understand how to interpret the results of linear models.

Multiple Linear Regression

In this lesson, you'll learn to apply multiple linear regression models in Python. Then you'll learn how to interpret the results and understand if your model fits well.

Logistic Regression

In this lesson, you'll learn to apply logistic regression models in Python as well as how to interpret logistic regression results.

Model Salary Data with Linear Regression

In this project, you will build a linear model and interpret the results of the model. Specifically, you will look at what variables are related to salaries.