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Learner Reviews & Feedback for Linear Regression with Python by Coursera Project Network

4.6
stars
415 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 4, 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 24, 2020

Great course.

Learn new topics like forward passing and backward passing to update parameters for prediction in regression

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