Humans can learn new things with a small set of examples. When presented with stimuli, humans seem to be able to understand new concepts quickly and then recognize variations of those concepts in the future. A child can learn to recognize a dog from a single picture, but a machine learning system needs a lot of examples to learn the features of a dog and recognize them in the future. Machine learning, as a field, has been highly successful at a variety of tasks, such as classification and web searching, as well as image and speech recognition. Often, however, these models do not perform well without a large amount of data (examples) to learn from. The primary motivation behind this book is to train a model with very few examples that is capable of generalizing to unfamiliar categories without extensive retraining.
Deep learning has played an important...
