Gradient descent gives one way of minimizing J. Let’s discuss a second way of doing so, this time performing the minimization explicitly an…

Linear regression with multiple variables is also known as "multivariate linear regression". We now introduce notation for equations where …

The inverse of a matrix A is denoted A-1. Multiplying by the inverse results in the identity matrix. A non square matrix does not have an i…

. Matrices are not commutative: A∗B != B∗A . Matrices are associative: (A∗B)∗C = A∗(B∗C)(A∗B)∗C=A∗(B∗C) The identity matrix, when multiplie…

The above matrix has four rows and three columns, so it is a 4 x 3 matrix. So vectors are a subset of matrices. The above vector is a 4 x 1…

So we have our hypothesis function and we have a way of measuring how well it fits into the data. Now we need to estimate the parameters in…

To establish notation for future use, we’ll use x^i to denote the “input” variables , also called input features, and y^i to denote the “ou…

Supervised learning and Unsupervised learning. In supervised learning, we are given a data set and already know what our correct output sho…

Arthur Samuel described machine learning as: "the field of study that gives computers the ability to learn without being explicitly program…