Over the past decade, Machine Learning (ML) has increasingly been used to power a variety of products such as automated support systems, translation services, recommendation engines, fraud detection models and many, many more.
Surprisingly, there aren’t many resources available to teach engineers and scientists how to build such products. Many books and classes will teach how to train ML models, or how to build software projects, but very few blend both worlds to teach how to build practical applications that are powered by ML.
This book goes through every step of this process, and aims to help you accomplish each of them by sharing a mix of methods, code examples, and advice from me and other experienced practitioners. We’ll cover the practical skills required to design, build, and deploy ML powered applications. The goal of this book is to help you succeed at every part of the ML process.
What This Book Covers
To cover the topic of building applications powered by ML, the focus of this book is concrete and practical. In particular, this book aims to illustrate the whole process of building ML powered applications.
To do so, I will first describe methods to tackle each step in the process. Then, I will illustrate these methods using an example project as a case study. The book also contains many practical examples of ML in industry, and features interviews with professionals that have built and maintained production ML models.