Python - Linear Regression
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In this video, I’m showing you a straightforward way to calculate linear regression using Python. Whether you're new to this or need a refresher, this tutorial is for you!
Simple Explanation of Linear Regression:
Linear regression is a method used to understand the relationship between two variables. Imagine you have some data points and want to draw a straight line that best fits these points. This line helps you predict values of one variable based on the other. For example, if you're predicting someone's weight based on their height, linear regression will find the best straight line that represents this relationship.
🔗 Blog article a bit related to the video:
https://www.vitoshacademy.com/python-...
📊 GitHub repository with the code:
https://github.com/Vitosh/Python_pers...
📝Contents:
Introduction - 0:05
Example with 5 values only - 1:57
Calculating residuals manually with Excel - 8:48
Plotting values and prediction line - 13:50
Calculating residuals with model.fit - 15:03
Plotting squares - 17:10
Plotting both lines - 17:32
Slope and intersept of the model - 19:58
Example with 100 (later 1K) values - 20:55
Plotting the trained, tested and predicted values - 27:38
Summary - 35:50
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💡 #python #linear-regression #fitting #machinelearning #programming 🎨
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