Course · Intermediate
Linear Regression Modeling in Python
In this course, you will learn how to build, evaluate, and interpret the results of a linear regression model, as well as using linear regression models for inference and prediction.
- Intermediate friendly
- 4 hrs
- 4 lessons
- 1 project
- Premium
Course overview
Model and interpret relationships between variables by constructing, evaluating, and applying linear regression for inference and prediction.
What's inside
4 lessons · 1 project
- 01 49 minIntroduction to Linear Regression
Understand the basic concepts, terms, and motivations behind linear regression.
- 02 37 minInterpreting Regression Parameters
In this lesson, we learn how to fit a linear regression model using the scikit-learn library and how to interpret the parameters.
- 03 34 minChecking Linear Regression Fit
In this lesson, we learn how to evaluate a model based on the calculated residuals.
- 04 45 minApplying Linear Regression Models
Learn how to test a model's predictive ability, and iterate to make better predictions.
- 05 36 minGuided Project: Predicting Insurance Costs Project
For this project, you'll step into the role of a data analyst tasked with developing a model to predict patient medical insurance costs based on demographic and health data.
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