Artificial Intelligence in Finance

Chapter 1. Artificial Intelligence

This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.

David Silver et al. (2016)

This chapter introduces general notions, ideas, and definitions from the field of artificial intelligence (AI) for the purposes of this book. It also provides worked-out examples for different types of major learning algorithms. In particular, “Algorithms” takes a broad perspective and categorizes types of data, types of learning, and types of problems typically encountered in an AI context. This chapter also presents examples for unsupervised and reinforcement learning. “Neural Networks” jumps right into the world of neural networks, which not only are central to what follows in later chapters of the book but also have proven to be among the most powerful algorithms AI has to offer nowadays. “Importance of Data” discusses the importance of data volume and variety in the context of AI.

Algorithms

This section introduces basic notions from the field of AI relevant to this book. It discusses the different types of data, learning, problems, and approaches that can be subsumed under the general term AI. Alpaydin (2016) provides an informal introduction to and overview of many of the topics covered only briefly in this section, along with many examples.

Types of Data

Data in general has two major components:

Features

Features data (or input data) ...