Learn the skills necessary to design build and deploy applications powered by machine
learning (ML). Through the course of this hands-on book you'll build an example ML-driven
application from initial idea to deployed product. Data scientists software engineers and
product managers—including experienced practitioners and novices alike—will learn the tools
best practices and challenges involved in building a real-world ML application step by step.
Author Emmanuel Ameisen an experienced data scientist who led an AI education program
demonstrates practical ML concepts using code snippets illustrations screenshots and
interviews with industry leaders. Part I teaches you how to plan an ML application and measure
success. Part II explains how to build a working ML model. Part III demonstrates ways to
improve the model until it fulfills your original vision. Part IV covers deployment and
monitoring strategies. This book will help you: Define your product goal and set up a machine
learning problem Build your first end-to-end pipeline quickly and acquire an initial dataset
Train and evaluate your ML models and address performance bottlenecks Deploy and monitor your
models in a production environment
