Practical Data & AI for Engineers
Applied Machine Learning, Data Pipelines, and AI Integration in Engineering Projects
In today’s engineering world, data and artificial intelligence are no longer optional — they are essential. Practical Data & AI for Engineers bridges the gap between traditional engineering practice and the new era of intelligent automation, predictive analytics, and digital twins.
This hands-on guide provides a real-world, engineering-focused introduction to applied machine learning, data management, and AI-driven solutions. It shows how engineers across disciplines — electrical, mechanical, civil, and industrial — can use data pipelines, models, and automation tools to enhance design, operations, and maintenance.
How to collect, clean, and manage engineering data from sensors, PLCs, and SCADA systems.
Building data pipelines for real-time monitoring and analytics.
Practical machine learning models for predictive maintenance, fault detection, and optimization.
AI integration strategies for control systems, HVAC, power distribution, and manufacturing.
Tools and workflows for implementing AI at scale — from the field to the cloud.
With clear diagrams, simplified explanations, and step-by-step use cases, this book helps engineers adopt AI confidently without requiring advanced programming skills.
Whether you’re a design engineer, facility manager, or project leader, this book will guide you through every stage of your digital transformation — from understanding data sources to deploying your first AI model.
Part of the Practical Engineering Series by the Practicing Engineers Network (PEN)
Your trusted reference for engineering design, calculations, and modern technology applications.
This book is part of the Practical Engineering Series by the Practicing Engineers Network (PEN) — a collective of professionals dedicated to bridging the gap between theory and practice across all branches of engineering. Whether you’re an electrical engineer automating substation monitoring, a mechanical engineer building predictive models for pumps, or a civil engineer exploring AI-based structural analysis, you’ll find practical insights tailored to your domain.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Paperback. Condición: new. Paperback. Practical Data & AI for EngineersApplied Machine Learning, Data Pipelines, and AI Integration in Engineering ProjectsIn today's engineering world, data and artificial intelligence are no longer optional - they are essential. Practical Data & AI for Engineers bridges the gap between traditional engineering practice and the new era of intelligent automation, predictive analytics, and digital twins.This hands-on guide provides a real-world, engineering-focused introduction to applied machine learning, data management, and AI-driven solutions. It shows how engineers across disciplines - electrical, mechanical, civil, and industrial - can use data pipelines, models, and automation tools to enhance design, operations, and maintenance.What You'll LearnHow to collect, clean, and manage engineering data from sensors, PLCs, and SCADA systems.Building data pipelines for real-time monitoring and analytics.Practical machine learning models for predictive maintenance, fault detection, and optimization.AI integration strategies for control systems, HVAC, power distribution, and manufacturing.Tools and workflows for implementing AI at scale - from the field to the cloud.With clear diagrams, simplified explanations, and step-by-step use cases, this book helps engineers adopt AI confidently without requiring advanced programming skills.Whether you're a design engineer, facility manager, or project leader, this book will guide you through every stage of your digital transformation - from understanding data sources to deploying your first AI model.Part of the Practical Engineering Series by the Practicing Engineers Network (PEN)Your trusted reference for engineering design, calculations, and modern technology applications. This book is part of the Practical Engineering Series by the Practicing Engineers Network (PEN) - a collective of professionals dedicated to bridging the gap between theory and practice across all branches of engineering. Whether you're an electrical engineer automating substation monitoring, a mechanical engineer building predictive models for pumps, or a civil engineer exploring AI-based structural analysis, you'll find practical insights tailored to your domain. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798269278841
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Librería: California Books, Miami, FL, Estados Unidos de America
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9798269278841
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9798269278841
Cantidad disponible: Más de 20 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. Practical Data & AI for EngineersApplied Machine Learning, Data Pipelines, and AI Integration in Engineering ProjectsIn today's engineering world, data and artificial intelligence are no longer optional - they are essential. Practical Data & AI for Engineers bridges the gap between traditional engineering practice and the new era of intelligent automation, predictive analytics, and digital twins.This hands-on guide provides a real-world, engineering-focused introduction to applied machine learning, data management, and AI-driven solutions. It shows how engineers across disciplines - electrical, mechanical, civil, and industrial - can use data pipelines, models, and automation tools to enhance design, operations, and maintenance.What You'll LearnHow to collect, clean, and manage engineering data from sensors, PLCs, and SCADA systems.Building data pipelines for real-time monitoring and analytics.Practical machine learning models for predictive maintenance, fault detection, and optimization.AI integration strategies for control systems, HVAC, power distribution, and manufacturing.Tools and workflows for implementing AI at scale - from the field to the cloud.With clear diagrams, simplified explanations, and step-by-step use cases, this book helps engineers adopt AI confidently without requiring advanced programming skills.Whether you're a design engineer, facility manager, or project leader, this book will guide you through every stage of your digital transformation - from understanding data sources to deploying your first AI model.Part of the Practical Engineering Series by the Practicing Engineers Network (PEN)Your trusted reference for engineering design, calculations, and modern technology applications. This book is part of the Practical Engineering Series by the Practicing Engineers Network (PEN) - a collective of professionals dedicated to bridging the gap between theory and practice across all branches of engineering. Whether you're an electrical engineer automating substation monitoring, a mechanical engineer building predictive models for pumps, or a civil engineer exploring AI-based structural analysis, you'll find practical insights tailored to your domain. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798269278841
Cantidad disponible: 1 disponibles