If you are reading this, then you are probably aware that ML has become a strategic capability in many industries, including the investment industry. The explosion of digital data that drives much of the rise of ML is having a particularly powerful impact on investing, which already has a long history of using sophisticated models to process information. The scope of trading across asset classes implies that a vast range of new, alternative data may be relevant in addition to the market and fundamental data that used to be the focus of the analytical efforts.

You may have also come across the insight that the successful application of ML or data science requires the integration of statistical knowledge, computational skills, and domain expertise at the individual or team level. In other words, it is essential to ask the right questions, identify and understand the data that may provide the answers, deploy a broad range of tools to obtain results, and interpret them in a way that leads to the right decisions. 

Consequently, this book takes an integrated perspective on the application of ML to the domain of investment and trading. In this section, we will lay out what to expect, how it goes about achieving its objectives, and what you need to both meet your goals and have fun in the process.