Machine Learning Fundamentals (ASQ's Pocket Guide Series)

Artificial intelligence (AI) and machine learning (ML) are transforming how organizations solve problems, improve processes, and make smarter decisions. But for many professionals, the challenge is knowing where these tools fit into the systems already in place. This practical pocket guide translates machine learning concepts into real-world applications for quality and manufacturing professionals. Learn how ML can support predictive insights, root cause analysis, process optimization, and better operational decision-making.

In this pocket guide, you’ll find:

• Core ML concepts explained in plain language
• Real-world industry examples
• Nine methods for applying ML to real business challenges
• A handy glossary of essential terms

Nicole M. Radziwill is Co-Founder and CTAIO of team-x.ai, enabling AI transformation at scale through quality-first AI and team excellence. A former SVP and Chief Data Scientist and tenured Associate Professor of Data Science and Production Systems, Nicole is an Academician in the International Academy of Quality (IAQ) and a Fellow of the American Society for Quality (ASQ). She has a PhD in Quality Systems and is the author of data science and statistics textbooks, as well as Connected, Intelligent, Automated: The Definitive Guide to Digital Transformation and Quality 4.0 (2020) and Data, Strategy, Culture & Power (2024).