This chapter covers:
- Describing the structure and objectives of this book
- Defining what machine learning is
- Explaining why machine learning is important
- Exploring why machine learning projects are different
- Listing other approaches to machine learning development
This book describes an end-to-end process for delivering a machine learning (ML) project to solve a business problem that’s big enough and difficult enough to need a team. The rapid surge of interest in ML and the sudden change in ML’s capability with the development of practical deep neural networks documented by LeCun et al. [1] and other advanced methods such as MCMC algorithms discussed by Carpenter et al. [2] means that there are a lot of new opportunities for ML projects. So, a lot of people are going to be managing these projects, and this is a guidebook for them.