Linear Regression, Machine Learning, Introduction, Gradient Descent.
the size 𝛼 towards the direction of the negative gradient and have a new w_1. The model using w_1 as a parameter should then have a smaller error compared to the real data, than the first model. We go on with this algorithm until we find a model that is sufficiently close to our data. A sketch of