I call this a cost function rather than the cost function because one cost function does not fit all. Cost functions vary depending on the kind of data set or machine learning model. For the purposes of machine learning, cost functions become the algorithms that measure the performance of hypotheses. This equation comes […]

# Tag: regression

The very first formula I learned in machine learning (and the first time I tried writing in LaTeX!) So pretty cool, but what does it mean? This is an example of a univariate hypothesis. ‘Univariate’ is a fancy way of saying that I have one variable (let’s call it ‘x’ for now) that […]

Linear regression, cost function and gradient descent sum up the first two weeks of Professor Ng’s Machine Learning class on Coursera. Since I am not aspiring to be a mathematician, I am going to refer to them as algorithms. Each of these algorithms has a particular place when designing a machine learning solution. Linear regression, […]