Machine Learning System Design: With End-To-End Examples -- Valerii Babushkin

<b>Get the big picture and the important details with this end-to-end guide for designing highly effective, reliable machine learning systems.</b> <p/>From information gathering to release and maintenance, <i>Machine Learning System Design</i> guides you step-by-step through every stage of the machine learning process. Inside, you'll find a reliable framework for building, maintaining, and improving machine learning systems at any scale or complexity. <p/>In <i>Machine Learning System Design: With end-to-end examples</i> you will learn: <p/>- The big picture of machine learning system design<br> - Analyzing a problem space to identify the optimal ML solution<br> - Ace ML system design interviews<br> - Selecting appropriate metrics and evaluation criteria<br> - Prioritizing tasks at different stages of ML system design<br> - Solving dataset-related problems with data gathering, error analysis, and feature engineering<br> - Recognizing common pitfalls in ML system development<br> - Designing ML systems to be lean, maintainable, and extensible over time <p/> Authors <b>Valeri Babushkin</b> and <b>Arseny Kravchenko</b> have filled this unique handbook with campfire stories and personal tips from their own extensive careers. You'll learn directly from their experience as you consider every facet of a machine learning system, from requirements gathering and data sourcing to deployment and management of the finished system. <p/> Purchase of the print book includes a free eBook in P