Intro to Machine learning

It has been long understood that learning is a key element of intelligence. This holds both for natural intelligence - we all get smarter by learning and artificial intelligence. The roots of machine learning are in statistics, which can also be thought of as the art of extracting knowledge from data. Especially methods such as linear regression and Bayesian statistics, which are both already more than two centuries old (!), are even today at the heart of machine learning. For more examples and a brief history, see the timeline of machine learning (Wikipedia). Examples include predicting the number of people who will click a Google ad based on the ad content and data about the user's prior online behavior, predicting the number of traffic accidents based on road conditions and speed limit, or predicting the selling price of real estate based on its location, size, and condition.