Linear Regression Algorithm Tutorial | Linear Regression Explained

In this video, we'll talk about Linear Regression. It is one of the most basic Machine Learning algorithm and very intuitive. The video explains concepts such as the cost function, gradient descent and much more. The implementation of the algorithm will be seen in the next video!
A practical guide on how to implement linear regression in Python - data set and code are provided.

References -

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[kantorobo]

let's grab a cup of tea, and learn

[kantorobo]

Thanks for the explanation do you have a link for the notebook?

[oliwanekenobi]

I have never understood why a linear regression was dubbed a part of the 'machine learning' toolbox. There is no learning (i.e. more accurate predictions as the model is applied to another set of data. The model gets better with more data, but that is because of the properties of the estimator). Indeed, we even have a closed-form solution for the linear regression : beta=(x'x) *(x'y) ^(-1)! Any numerical optimization will therefore be inferior to it.
I believe that one should simply say that "linear regression is taken from econometrics". Granted, to deepen the body of knowledge in machine learning, one needs to start somewhere, but claiming that a linear regression is machine learning is, in my view, an overstatement. Or is machine learning simply numerical optimization?