Machine Learning System Design

You will learn how to:

• See the big picture in ML system design
• Analyze tasks and choose optimal ML solutions
• Pass interviews on ML system design
• Select metrics and evaluation criteria
• Properly prioritize at different stages of the project
• Work with data issues: collection, error analysis, feature generation
• Avoid common mistakes when developing ML systems
• Design systems that are easy to maintain and develop

About the Technologies

Developing a machine learning system is a complex process requiring knowledge in engineering, data analysis, and model operation. Whether you are creating an ML system from scratch or integrating a model into an existing application, you will work with large volumes of data, set up testing, monitoring, and deployment processes. This book will be your guide in this process.

Features

The book includes practical checklists, examples from real projects, tips for interviews, as well as "campfire tales" - practical stories and observations from the author accumulated over years of experience.