"Machine learning can be broadly defined as computational methods using experience to improve performance or to make accurate predictions. Here, experience refers to the past information available to the learner, which typically takes the form of electronic data collected and made avalaible for analysis. This data could be in the form of digitized human-labeled training sets, or other types of information obtained via interactin with the environment. In all cases, its quality and size are crucial to the success of the predictions made by the learner."