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Konieczny B: Data Engineering Design
Patterns

Data Engineering Design Patterns

Recipes for Solving the Most Common Data Engineering Problems

This book offers a comprehensive and application-oriented exploration of Artificial Intelligence and Natural Language Processing (NLP), addressing both foundational principles and modern, data-driven methodologies. It is designed to equip readers with a deep understanding of how intelligent systems learn from data, interpret human language, and support automated decision-making across real-world contexts.Natural Language Processing for Business and Organizations: Research and Innovation cover key areas such as machine learning, deep learning, text representation, language modeling, information extraction, sentiment analysis, and AI-driven analytics, while also discussing system design considerations for deploying NLP solutions at scale. Through carefully structured chapters, the book integrates theoretical insights with practical examples, case studies, and applied workflows, enabling readers to translate algorithms and models into effective AI applications. Written by a team of academic researchers and industry practitioners, the book emphasizes responsible and value-driven AI, including ethical considerations, data quality, and model evaluation.This book is written for advanced undergraduate and postgraduate students, researchers, and professionals seeking to build, evaluate, and apply AI and NLP systems in academic, enterprise, and societal domains.

Research and Innovation

Natural Language Processing for Business and Organizations

Rapidly transform your analytics teams to deliver AI-driven insights.

The AI-driven Data Team by Nicholas Kelly is a proven-to-work playbook for data and analytics leaders who want to align analytics capabilities with the demands of an AI-powered business environment. Written for leaders accountable for data, analytics and business intelligence, this book provides tools for diagnosing capability gaps among data analytics teams, modernizing legacy stacks and delivering AI-driven insights to help organizations make better decisions. 

You'll learn how to:
- Diagnose skills gaps and map AI-augmented career paths
- Integrate modern AI tools with existing analytics stacks
- Launch six revenue-driving and cost-focused pilots in 90 days
- Embed ISO and NIST-aligned governance without slowing innovation
- Apply ROI calculators, governance checklists and sprint planners

Drawing on expert insights and real-world applications, this book helps you upskill your analysts, strengthen AI governance and provide AI-driven insights that drive real results.

Themes include: AI strategy, data governance, analytics leadership, ROI from AI, organizational transformation, executive decision-making

Improve Your Analytics with AI

The Ai-Driven Data Team

Easy and effective strategies for using AI chatbots Turn your business into a 24/7 customer service powerhouse with AI chatbots that work around the clock! Perfect for anyone drowning in customer emails or missing sales opportunities while they sleep, AI Chatbots For Dummies explains how to build intelligent chatbots from scratch - no coding required. You'll discover how major companies use chatbots to boost efficiency and customer satisfaction and learn to create your own automated assistants for customer service, lead generation, and marketing campaigns that practically run themselves. Inside ... <ul><li>Build no-code solutions</li><li>Create 24/7 customer support</li><li>Accelerate lead generation</li><li>Convert leads into customers</li><li>Reduce overhead and workload</li><li>Improve customer satisfaction</li><li>Scale your company</li><li>Integrate the newest tools</li></ul>

AI ChatBots For Dummies

Marketing Technology is the ideal textbook for understanding technology-driven marketing strategy in a digital-first world. This textbook provides upper-level undergraduate and postgraduate students with a comprehensive understanding of how innovation shapes marketing strategy and practice in the modern business environment. Blending theory, strategic models and applied insights, this textbook explores the technologies transforming marketing from: artificial intelligence and machine learning to blockchain, automation and augmented, virtual and mixed realities. Students will learn how to use data and critical thinking to deliver measurable impact and build customer trust in an era of continuous digital evolution. Designed for academic alignment, with key terms, key points, exercises, and reflective questions and real-world application, this textbook includes: 
- Detailed coverage of the historical connection between technology and marketing, big data, neuromarketing, smart devices for enhanced consumer engagement, Internet of Things (IoT) and their role in contemporary marketing strategy
- Frameworks for optimizing campaign performance through analytics, automation and return on investment measurement
- Ethical perspectives are explored in each chapter highlighting responsible and transparent use of marketing technology
- Online lecturer resources include presentation slides Whether studying digital marketing, strategic marketing or marketing management, Marketing Technology by Ediz Edip Akçay, equips students with the expertise and confidence to analyse, apply and innovate with the tools shaping the future of marketing.

Integrating Martech for Transformational Marketing

Marketing Technology

AI Marketing Essentials: Concepts and Practice for the Digital Age explores the dynamic intersection of AI technology and marketing, providing theoretical frameworks for understanding its fast-growing potential in the development and implementation of successful marketing strategies.By guiding the reader through the principles, tools, and techniques of AI in marketing, this comprehensive textbook will help readers understand how they can leverage AI to transform different marketing functions throughout the lifecycle of a product, from initial strategy to product development, pricing, and distribution. This book combines theoretical understanding with insights from industry to reinforce learning, featuring real-life examples and case studies from different industries and countries across the world. In the first section, the book introduces the AI marketing discipline and how it has evolved. It explains the fundamental AI concepts such as machine learning, big data, NLP, and algorithms, which are crucial to understanding how they work.In further sections, the applications of these technologies are explored and explained in various marketing functions through case studies from multiple industries and concepts from marketing and technology. The application of these functions across retail, products, service, and business-to-business operations is then explored, followed by a critical discussion of the social and ethical dimensions and future directions for the use of AI in marketing.An accessible guide for understanding the AI marketing space, this book will suit undergraduate and postgraduate students as well as marketing professionals looking to build foundational knowledge in the concepts and impact of AI in marketing.

Concepts and Practice for the Digital Age

AI Marketing Essentials

Artificial Intelligence for Science and Engineering Applications

The accelerating global demand for sustainable solutions has catalyzed the integration of emerging technologies with sustainability-driven innovations. This book explores the intersection of technology, engineering, and environmental responsibility through six critical themes: Artificial Intelligence and Machine Learning for Sustainability, Cloud Computing Technologies, Sustainable Energy Technologies, Sustainable Materials and the Built Environment, Sustainable Actions, and Innovative Engineering and Technology.Artificial intelligence and machine learning play a pivotal role in optimizing resource management and enabling low-carbon decision-making, while cloud computing technologies provide scalable platforms for collaboration and innovation. Sustainable energy technologies such as solar, wind, and bioenergy are examined as vital pathways toward clean power generation. The discussion extends to sustainable materials and the built environment, emphasizing eco-friendly design and circular economy principles. The book also highlights sustainable actions driven by policy, behavioral change, and community engagement. Together, these domains represent a multidisciplinary pathway toward achieving global sustainability goals, fostering a balance between technological advancement and ecological preservation.This book is a key resource for leaders, academia, policymakers, professionals, and researchers to advance sustainable development through science, technology, and engineering. It provides valuable insights for integrating AI, renewable energy, and sustainable engineering into practical applications for a greener future.

Emerging Frontiers in Sustainable Energy, Smart Systems, and Green Technology

Data centres are involved in the sorting, sifting, storage, aggregation, and monetization of transactional data critical to data capitalism. Tucked away in high-rise buildings or peri-urban areas, data centres are largely invisible and fundamentally resource-intensive, and deploy extractive, energy-intensive technologies. In the context of artificial intelligence, data centre energy consumption has skyrocketed. Data Centre Entanglements addresses external challenges, specifically, contemporary geopolitical struggles between China and the USA to become the world's data hegemon and supply chain issues related to critical minerals and semiconductors, as well as internal issues such as data centre sustainability, which is particularly acute in countries facing significant water and power stresses. Given their essential infrastructure status in many countries, data centres are immune to public scrutiny, leading to transparency and accountability issues. The special relationship that data centres--in particular, hyperscale data centres owned by Big Tech--have with the State is reflected in the migration of public data to privately-owned data centres. Thomas focuses on this relationship in the context of data localization, data sovereignty, risk, the politics of greening and renewable energy, and incentives such as access to subsidized land, tax breaks, and unrestricted labour supply. The book concludes with a discussion on the democratization of data centres and makes a case for diversity in data centre ownership, including community-based ownership.

Geopolitics, Vulnerabilities, Sustainability, Activisms

Data Centre Entanglements

Transforming Tourism and Hospitality: AI-Powered Service Delivery Innovations explores the profound impact of Artificial Intelligence, IoT, and emerging technologies on the tourism and hospitality industry. This edited volume presents scholarly insights and real-world case studies on AI-driven customer service, sustainable operations, smart maintenance, fraud detection, dynamic pricing, and enhanced guest security. It examines tools like VR, blockchain, and AI-powered HR systems, emphasizing ethical adoption and human-AI collaboration. With robust empirical validation and practical examples, the book offers a valuable resource for academics, professionals, and policymakers seeking to understand and implement AI innovations in service delivery across the sector.

AI-Powered Service Delivery Innovations

Transforming Tourism and Hospitality

How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

How deep learning from Google Translate to driverless cars to personal cognitive assistants is changing our lives and transforming every sector of the economy.

The Deep Learning Revolution

Transforming Healthcare: Digital Health and Emerging Technologies" is a pioneering book designed to explore the dynamic and rapidly evolving intersection of healthcare and technology. This comprehensive guide delves into essential topics such as digital health, data privacy, big data analytics, artificial intelligence, quantum computing, and more. Each chapter provides in-depth coverage of key concepts, practical applications, and real-world case studies, equipping healthcare professionals, informaticists, and students with the knowledge and skills required to navigate and excel in the future of healthcare. What sets this book apart is its interdisciplinary approach, making it an ideal resource for pharmacy, medicine, nursing, and business healthcare classes and professionals. The inclusion of real-world datasets, such as the Belmont Data Collaborative's HTN in Nashville dataset, and detailed project suggestions ensures that readers gain practical, hands-on experience. Additionally, the book addresses current and future trends, challenges, and ethical considerations, making it an indispensable resource for those seeking to understand and lead in the digital transformation of healthcare. As the healthcare industry increasingly relies on technology to improve patient outcomes, enhance efficiency, and ensure data security, this book fills a critical need by providing a thorough and practical foundation in digital health and emerging technologies.

Digital Health and Emerging Technologies

Transforming Healthcare

Beyond the Human Touch: AI's Revolution in Healthcare provides a comprehensive, accessible, and engaging exploration of how Artificial Intelligence (AI) is transforming healthcare. The book aims to serve as a definitive guide for healthcare professionals, policymakers, researchers, and students, offering insights into the practical applications, ethical considerations, and future potential of AI in the healthcare sector. This book benefits the healthcare and AI communities by:¿ Providing a thorough understanding of how AI technologies are being integrated into various aspects of healthcare.¿ Offering practical insights and strategies for implementing AI in clinical and administrative settings.¿ Highlighting the ethical and regulatory considerations necessary for responsible AI adoption.¿ Envisioning the future of AI in healthcare, including its potential to address global health disparities.

AI's Revolution in Healthcare

Beyond the Human Touch

Data Engineering Design Patterns

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