Back to Linear Regression with Python
Learner Reviews & Feedback for Linear Regression with Python by Coursera Project Network
428 ratings
About the Course
In this 2-hour long project-based course, you will learn how to implement Linear Regression using Python and Numpy. Linear Regression is an important, fundamental concept if you want break into Machine Learning and Deep Learning. Even though popular machine learning frameworks have implementations of linear regression available, it's still a great idea to learn to implement it on your own to understand the mechanics of optimization algorithm, and the training process.
Since this is a practical, project-based course, you will need to have a theoretical understanding of linear regression, and gradient descent. We will focus on the practical aspect of implementing linear regression with gradient descent, but not on the theoretical aspect.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Top reviews
AS
Jun 5, 2020
Good refresher course on linear regression! It would have been great had the Instructor covered few of the statical tests or multivariate regression model.
PP
May 25, 2020
Great course.Learn new topics like forward passing and backward passing to update parameters for prediction in regression
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