You may be familiar with the notion of supervised learning, which is the most studied and well-known machine learning problem. Its basic question is, how do you automatically build a function that maps some input into some output when given a set of example pairs? It sounds simple in those terms, but the problem includes many tricky questions that computers have only recently started to address with some success. There are lots of examples of supervised learning problems, including the following:
- Text classification: Is this email message spam or not?
- Image classification and object location: Does this image contain a picture of a cat, dog, or something else?
- Regression problems: Given the information from weather sensors, what will be the weather tomorrow?
- Sentiment analysis: What is the customer satisfaction level of this review?
These questions may look different, but they share the same idea—we have many examples of input and...