Hello and welcome to section 3 on Machine Learning. Machine learning is a branch of artificial intelligence that deals with learning patterns and rules from training data. Its origins date back to the middle of the last century, but it's really in the last decade that companies have used it massively for their products. This revolution of machine learning has been enabled by really three factors. First of all, memory storage has become really cheap and accessible. Second, computing power has also become really cheap and accessible. And third, sensors, phones, and web application have produced a lot of data which has contributed to training these machine learning models. So the same is true for deep learning. 

In the last few years, we have seen a revolution in the revolution, with deep learning enabled by the same three factors kind of taking the stage and becoming very popular. Before we dive into deep learning and neural nets, we need to make sure we speak the same language and we are familiar with some concepts that are general in machine learning. So if you're familiar with things like, "What is a regression? What is a classification?" How to do a cross validation and how to draw a computer matrix, feel free to skip this section and just check your knowledge with the exercise. Make sure you understand fully what cost function and parameter optimizations are, because these two are really the pillars upon which we'll build the rest of the course. So let's get started with section 3, Machine Learning.