Master Multiple Linear Regression in Python with scikit-learn ๐
Learn how to perform multiple linear regression in Python using scikit-learn with the Boston Housing dataset. Perfect for beginners looking to understand predictive modeling!

Algovibes
2.5K views โข Sep 30, 2020

About this video
This video is showing how to implement a linear regression using sci-kit learn using the boston house price dataset which is an included dataset for practicing Machine Learning Algorithms. The dataset is suitable for regression tasks.
Also covered is the Mean squared error by hand and R-squared by hand.
To better follow along I recommend to watch the video on the simple linear regression on this channel first and also the video on the R-squared.
If you have any questions or issues don't hesitate to drop me a comment.
0:00 - 2:45 Understanding the data & define independent/dependent variable
2:45 - 5:20 Training and testing data split
5:20 - 6:20 Building the model
6:20 - 7:30 Comparison of predicted and actual y values
7:30 - 08:32 Mean squared error
08:32 -10:30 R-squared
10:30-12:50 Understanding the model
Video on simple linear regression:
https://youtu.be/iyfk62n7Lz8
Video on R-Squared:
https://youtu.be/15XH4ATeFmU
#Python # DataScience #sklearn
Also covered is the Mean squared error by hand and R-squared by hand.
To better follow along I recommend to watch the video on the simple linear regression on this channel first and also the video on the R-squared.
If you have any questions or issues don't hesitate to drop me a comment.
0:00 - 2:45 Understanding the data & define independent/dependent variable
2:45 - 5:20 Training and testing data split
5:20 - 6:20 Building the model
6:20 - 7:30 Comparison of predicted and actual y values
7:30 - 08:32 Mean squared error
08:32 -10:30 R-squared
10:30-12:50 Understanding the model
Video on simple linear regression:
https://youtu.be/iyfk62n7Lz8
Video on R-Squared:
https://youtu.be/15XH4ATeFmU
#Python # DataScience #sklearn
Video Information
Views
2.5K
Likes
57
Duration
12:51
Published
Sep 30, 2020
User Reviews
4.5
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