In this video I give a step by step guide for beginners in machine learning on how to do Linear Regression using Gradient Descent method. First I start off with defining linear regression. Next we define the loss function and understand what it is. Then we tackle the gradient descent algorithm step by step with the help of an analogy for better understanding of the concept. Finally, we implement everything in Python, and create a machine learning model for a given data set and make predictions.
Written version of this tutorial:
https://towardsdatascience.com/linear-regression-using-gradient-descent-97a6c8700931
GitHub link for notebook and dataset:
https://github.com/chasinginfinity/ml-from-scratch/tree/master/02%20Linear%20Regression%20using%20Gradient%20Descent
If you would like to learn more about Linear Regression using Gradient Descent check out these links:
Mathematics of Gradient Descent - The Coding Train: https://www.youtube.com/watch?v=jc2IthslyzM
Linear Regression with Gradient Descent - The Coding Train: https://www.youtube.com/watch?v=L-Lsfu4ab74
How to do Linear Regression using Gradient Descent - Siraj Raval: https://www.youtube.com/watch?v=XdM6ER7zTLk
https://machinelearningmastery.com/linear-regression-tutorial-using-gradient-descent-for-machine-learning/
https://towardsdatascience.com/linear-regression-using-gradient-descent-in-10-lines-of-code-642f995339c0
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