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 problemBuild your first end-to-end pipeline quickly and acquire an initial datasetTrain and evaluate your ML models and address performance bottlenecksDeploy and monitor your models in a production environment
You can read this ebook online in a web browser, without downloading anything or installing software.
This ebook is available in file types:
This ebook is available in:
After you've bought this ebook, you can choose to download either the PDF version or the ePub, or both.
The publisher has supplied this book in DRM Free form with digital watermarking.
You can read this eBook on any device that supports DRM-free EPUB or DRM-free PDF format.
The publisher has supplied this book in encrypted form, which means that you need to install free software in order to unlock and read it.
To read this ebook on a mobile device (phone or tablet) you'll need to install one of these free apps:
To download and read this eBook on a PC or Mac:
The publisher has set limits on how much of this ebook you may print or copy. See details.