Overview

Manufacturing is entering a defining era shaped by data, intelligence, and autonomy. From predictive maintenance on the factory floor to real-time quality inspection and adaptive supply chains, Artificial Intelligence is no longer a futuristic concept-it is an operational necessity. The rapid evolution of machine learning, deep learning, and large language models has transformed how manufacturers design products, optimize processes, and respond to disruptions. With the emergence of generative systems such as OpenAI's models and agent-based orchestration frameworks inspired by research from organizations like DeepMind, we are witnessing a shift from analytics that merely predict outcomes to intelligent systems that can create, decide, and act. This book explores that shift-bridging traditional AI, Generative AI, and the new frontier of Agentic AI within the manufacturing context. AI, Generative AI and Agentic AI for Manufacturing: A Practical, Hands-on Approach Using Python is written for engineers, data scientists, operations leaders, and innovators who want more than theory. It offers a structured, application-driven journey-from foundational machine learning models to generative design, autonomous planning agents, and decision-making systems tailored to real-world industrial environments. Using Python as the core implementation language, the book emphasizes practical code examples, deployment considerations, and integration strategies for modern manufacturing ecosystems. Whether you are modernizing legacy production systems or building intelligent factories from the ground up, this guide is designed to equip you with the technical depth and practical tools needed to move from experimentation to measurable industrial impact.

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