Now that we have some idea of the inputs and outputs, let’s turn to machine learn-ing. What is learning, anyway? What is machine learning? These are philosophical questions, and we will not be too concerned with philosophy in this book; our emphasis is firmly on the practical. However, it is worth spending a few moments at the outset on fundamental issues, just to see how tricky they are, before rolling up our sleeves and looking at machine learning in practice.
Our dictionary defines “to learn” as