Search results for "Generative AI Engineering"
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R 763.00
Handbook of AI in Engineering Applications
There is a need to categorize artificial intelligence (AI) applications, tools, techniques, and algorithms based on their intended use in various design stages. Specifically, there is a need to explore AI techniques that are utilized for tasks such as designing, including but not limited to inspiration, idea and concept generation, concept evaluation, optimization, decision-making, and modeling. This includes things like generating ideas and concepts, evaluating those ideas, optimizing designs, making decisions, and creating models. This handbook brings all of these categories with compatible AI techniques, tools, and algorithms together in one place.Handbook of AI in Engineering Applications: Tools, Techniques, and Algorithms covers applications of AI in engineering and highlights areas such as future cities, mechanical system analysis, and robotic process automation, and presents the application of AI and the use of computerized systems that aim to simplify and automate the processes of design and construction of civil works. The handbook discusses the design and optimization of mechanical systems and parts, such as engines, gears, and bearings, which can be automated using AI and it explores the performance of robotics and automation systems which can be simulated and analyzed using AI to forecast behavior, spot future issues, and suggest changes. Rounding out this handbook is AI technology automation and how analyzing relevant data can provide a reliable basis for relevant personnel to carry out their work.This handbook fills the gap between R&D in AI and will benefit all stakeholders including industries, professionals, technologists, academics, research scholars, senior graduate students, government, and public healthcare professionals.
R 9,954.94
Practical Guide to Oracle AI Engineering
Learn how to build scalable data pipelines, train and deploy ML models, and deliver intelligent applications by leveraging the full power of Oracle's machine learning and GenAI services across cloud and database ecosystems.Key FeaturesApply practical data engineering methods to create intelligent enterprise applicationsMaster in-database ML, vectors, RAG, and GenAI agents through real-world examplesLearn about the ethics and security implications of AI technologyPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionIn A Practical Guide to Oracle AI Engineering, you'll learn how to tackle the challenges of building scalable, high-performance AI workflows in modern enterprises. Many organizations struggle to turn raw data into actionable insights while maintaining security, compliance, and operational efficiency. This book provides practical, end-to-end guidance for data engineers and architects to design, secure, implement, and optimize ML and GenAI solutions across Oracle Cloud, Oracle Database, and MySQL HeatWave.Written by multiple Oracle experts with deep experience in Oracle technologies and enterprise data platforms, this book walks you through real-world examples and hands-on workflows, from data preparation and in-database ML to deploying GenAI-powered applications and intelligent agents. You’ll gain skills in building pipelines, managing models, leveraging vector search for advanced AI use cases, and integrating AI into business applications with APEX and Oracle Digital Assistant. Advanced topics include scalable model deployment, serverless inference, monitoring, and MLOps best practices. By the end, you’ll be equipped to solve complex data challenges, accelerate AI adoption, and deliver measurable business impact through intelligent, production-ready solutions.What you will learnBuild scalable data pipelines for AI and ML workflowsPrepare and engineer data efficiently for in-database MLTrain, optimize, and deploy ML models across Oracle platformsUse GenAI and RAG-enabled GenAI agents for intelligent applicationsIntegrate AI vector search for semantic retrieval and recommendationsImplement ML inside the database, for improved performance and data currencyEnhance business applications with AI using APEX and Oracle Digital AssistantApply best practices for MLOps, monitoring, and secure AI workflowsWho this book is forThis book is for data engineers, architects, IT specialists, and data leaders responsible for building, managing, and optimizing enterprise data solutions. If you face challenges in designing secure, scalable pipelines or deploying ML and GenAI applications, this guide provides practical workflows and real-world strategies to accelerate AI adoption.
R 1,628.00
Recent Advancements in Computational Intelligence and Design Engineering
International Conference on Computational Intelligence and Design Engineering (ICCIDE 2023) is a multidisciplinary conference focused on bringing together recent advancements in the field of engineering, computer science and Mathematics. The key features of the conference include a common platform for research and innovation work related to next generation computation, Mathematics in computation as well as engineering research to achieve industry 5.0 mission. The conference covers different aspects of science and technology like applications of AI and ML for sustainable manufacturing and production systems, computational modelling, mathematics and computing.
R 3,085.80
Generative AI for Next-Gen Defence Strategies
This book aims to explore the manifold role of Generative AI in enhancing defence capabilities and its potential to transform future warfare. It is divided into three sections. The first discusses the fundamentals of Generative AI and its strategic significance in modern defence sector. This section sets the foundation for understanding how these technologies are shaping current defence strategies and providing a competitive edge. The second explores the application of Generative AI across military, aerospace and naval domain. This section starts by exploring the use of Generative AI for Strategic and Operational Planning, Battlefield Simulation and Training, and development of Autonomous Vehicles and Exoskeletons. The section also covers the use of Generative AI in Drone Swarms, Autonomous Navigation, and Mission Control, as well as its role in maintaining and monitoring Aerospace Infrastructure. Advanced applications such as Radar Systems, Underwater Drones, and Naval Robotics are also discussed in the section. Additionally, the predictive capabilities of Generative AI, including Trajectory Prediction and Failure Prediction for ships and aircraft, and its significance in Naval Warfare and Underwater Sensing have been explored. It also examines the critical role of Generative AI in Cyber Security and Network Defence. The last section of the book addresses the challenges of Generative AI in Defence and the ethical considerations that need to be addressed while using Generative AI in Defence sector. This section also critically assesses the potential threats posed by Generative AI in Cognitive Warfare, highlighting the need for robust ethical frameworks and policies to mitigate risks.The book will be useful for defence professionals, researchers, and technologists who want to understand the transformative potential of Generative AI in defence and attempts to inspire innovative thinking and foster a deeper understanding of the strategic value of Generative AI.
R 6,118.00
R 550.00
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R 763.00
Generative AI
From algorithms that draft clinical notes in seconds to autonomous agents that triage emergency room backlogs, artificial intelligence is quietly reshaping every facet of healthcare. Generative AI: Unlocking the Next Chapter in Healthcare is the first comprehensive guide to this revolution—charting how we got here, what’s working now, and where the technology could take us next.Drawing on frontline case studies from leading health systems, biotech labs, and tech giants, the book reveals how large language models, synthetic data engines, and multi agent ecosystems are boosting diagnostic accuracy, accelerating drug discovery, and personalizing patient engagement. It also confronts the hard questions—privacy, bias, liability, and the fear of “machines taking over”—offering clear, actionable frameworks for ethical, human centered deployment.Written for clinicians, executives, innovators, and policy makers and patients alike, this definitive volume distils the expertise of industry pioneers into an accessible roadmap. You’ll explore:• The evolution from early machine learning to today’s generative powerhouses• Real world wins—ambient documentation, AI assisted radiology, virtual nursing, and more• The players shaping the landscape: Epic, Google, Microsoft, NVIDIA, Salesforce, and a wave of insurgent startups• Guardrails that preserve trust, protect privacy, and keep humans in the loop• Bold yet plausible futures—from digital twin medicine to globe-spanning agent networksWhether you’re leading a hospital, building health tech solutions, a tech startup, or simply curious about the future of care, Generative AI: Unlocking the Next Chapter in Healthcare delivers the insight, inspiration, and practical guidance you need to thrive in the era where human empathy and machine intelligence work side by side.
R 7,565.42
Metaverse, Generative AI, and Brain-Computer Interfaces
This compelling exploration delves into the heart of cutting-edge technologies, specifically the Metaverse, Brain-Computer Interfaces (BCI), and generative artificial intelligence (AI). The authors unravel their transformative applications in shaping the future and contemplate how the next generation of virtual environments will manifest, as well as how the digital landscape can be affected.The book encompasses various examples of the Metaverse, brain-computer interfaces, and generative AI across diverse fields, including education, engineering, and medical science. In the dynamic realm of the Metaverse, where virtual realities converge, the book showcases how these innovations can transform the way we learn, interact, and build. Through Brain-Computer Interfaces (BCIs), users can directly interface with technology using neural signals, opening up new avenues for communication and control. Additionally, generative AI algorithms empower us to create immersive virtual environments and generate content with unprecedented creativity.Whether you're a student, educator, or industry professional, this book is your ticket to understanding and harnessing the power of the future. It provides a pathway for those who believe in the limitless possibilities that the Metaverse, BCI, and generative AI can bring to our daily experiences.
R 5,165.00
Handbook of AI in Engineering Applications
There is a need to categorize artificial intelligence (AI) applications, tools, techniques, and algorithms based on their intended use in various design stages. Specifically, there is a need to explore AI techniques that are utilized for tasks such as designing, including but not limited to inspiration, idea and concept generation, concept evaluation, optimization, decision-making, and modeling. This includes things like generating ideas and concepts, evaluating those ideas, optimizing designs, making decisions, and creating models. This handbook brings all of these categories with compatible AI techniques, tools, and algorithms together in one place.Handbook of AI in Engineering Applications: Tools, Techniques, and Algorithms covers applications of AI in engineering and highlights areas such as future cities, mechanical system analysis, and robotic process automation, and presents the application of AI and the use of computerized systems that aim to simplify and automate the processes of design and construction of civil works. The handbook discusses the design and optimization of mechanical systems and parts, such as engines, gears, and bearings, which can be automated using AI and it explores the performance of robotics and automation systems which can be simulated and analyzed using AI to forecast behavior, spot future issues, and suggest changes. Rounding out this handbook is AI technology automation and how analyzing relevant data can provide a reliable basis for relevant personnel to carry out their work.This handbook fills the gap between R&D in AI and will benefit all stakeholders including industries, professionals, technologists, academics, research scholars, senior graduate students, government, and public healthcare professionals.
R 3,297.00
R 811.00
R 397.00
R 1,527.00
ML and Generative AI in the Data Lakehouse
In today's race to harness generative AI, many teams struggle to integrate these advanced tools into their business systems. While platforms like GPT-4 and Google's Gemini are powerful, they aren't always tailored to specific business needs. This book offers a practical guide to building scalable, customized AI solutions using the full potential of data lakehouse architecture.Author Bennie Haelen covers everything from deploying ML and GenAI models in Databricks to optimizing performance with best practices. In this must-read for data professionals, you'll gain the tools to unlock the power of large language models (LLMs) by seamlessly combining data engineering and data science to create impactful solutions.Learn to build, deploy, and monitor ML and GenAI models on a data lakehouse architecture using DatabricksLeverage LLMs to extract deeper, actionable insights from your business data residing in lakehousesDiscover how to integrate traditional ML and GenAI models for customized, scalable solutionsUtilize open source models to control costs while maintaining model performance and efficiencyImplement best practices for optimizing ML and GenAI models within the Databricks platform
R 1,978.00
Deep Swarm and Evolution for Generative Artificial Intelligence
This book provides theoretical and practical knowledge about swarm and evolutionary approach of generative AI and Large Language Models (LLMs). The development of such tools contributes to better optimizing methodologies with the integration of several machinelearning and deep learning techniques. In particular, it discusses how the “emergence” concept can contribute to the improvement of AI.The book aims to model human cognitive f unction in terms of “emergence” and to explain the feasibility of AI. To this end, it focuses on human perceptions of “utility.” It describes the emergence of various cognitive errors, and irrational behaviours in the multiobjective situations. It also reviews the cognitive differences and similarities between humans and LLMs. Such studies are important when applying LLMs to real-world tasks that involve human cognition, e.g., financial engineering and market issues.The book describes the intelligent behaviour of living organisms. This is to clarify how to achieve AI in the direction of artificial life. It describes sexual selection, which is a well-known natural phenomenon that troubled Darwin, i.e., why evolutionarily useless items evolved such as peacock feathers and moose antlers etc. The book shows how sexual selection is extended as “novelty search” for the application of generative AI, i.e., the image generation with diffusion model. Real-world applications are emphasised. Empirical examples from real-world data show how the concept of deep swarm and evolution is successfully applied when addressing tasks from such recent fields as robotics, e-commerce Web Shop and image generation etc.
R 8,143.64
Building Generative AI Services with Fastapi
Ready to build production-grade applications with generative AI? This practical guide takes you through designing and deploying AI services using the FastAPI web framework. Learn how to integrate models that process text, images, audio, and video while seamlessly interacting with databases, filesystems, websites, and APIs. Whether you're a web developer, data scientist, or DevOps engineer, this book equips you with the tools to build scalable, real-time AI applications.Author Alireza Parandeh provides clear explanations and hands-on examples covering authentication, concurrency, caching, and retrieval-augmented generation (RAG) with vector databases. You'll also explore best practices for testing AI outputs, optimizing performance, and securing microservices. With containerized deployment using Docker, you'll be ready to launch AI-powered applications confidently in the cloud.Build generative AI services that interact with databases, filesystems, websites, and APIsManage concurrency in AI workloads and handle long-running tasksStream AI-generated outputs in real time via WebSocket and server-sent eventsSecure services with authentication, content filtering, throttling, and rate limitingOptimize AI performance with caching, batch processing, and fine-tuning techniques
R 1,596.00
R 916.00
R 580.00
Artificial Intelligence and System Engineering
This book presents cutting-edge research from CoMeSySo 2024, bridging theoretical insights and practical solutions across modern computing. Highlighting data-driven methodologies, innovative modelling, and robust optimization strategies, this book uniquely integrates interdisciplinary approaches to complex computational problems. Through real-world case studies, readers gain actionable insights applicable to diverse fields such as artificial intelligence, cybersecurity, e-learning, and operational logistics. Targeted at academic researchers, industry specialists, and graduate students, the compilation provides valuable frameworks and advanced analytical tools for enhancing performance, efficiency, and decision-making. The presented studies, encompassing adaptive network modelling, deep learning applications, and novel AI-driven frameworks, equip readers to tackle emerging challenges and drive future advancements effectively.
R 9,158.00
Generative AI for Cybersecurity
This book lays a systematic foundation for professionals, researchers, and industry readers who are interested the applications and implications of generative AI for cybersecurity. It covers the latest advances in generative AI and its applications, risks, and opportunities in cybersecurity.The authors first introduce the fundamental background of generative AI, the latest cybersecurity issues, and related potential applications in cybersecurity systems. Following this, they comprehensively review the state-of-the-art research and development, covering various aspects of generative AI applications in this area and related challenges and issues, such as training data availability, computational complexity, generalization to different scenarios, AI governance, quantum-empowered AI and many more. These discussions provide a strong understanding of recent advances in the two fields of generative AI and cybersecurity and the convergence of these domains, which will help readers to shape the field as it matures. Hands-on experiments presented throughout will also give them the practical skills for success. By leveraging its capabilities, readers can overcome challenges, understand the risks, enhance performance, and unlock new opportunities for handling the challenges of cybersecurity with generative AI. Consequently, they will be able to apply their knowledge to utilize generative AI in cybersecurity applications to prevent economic and other losses due to cyber risks such as phishing, fake news, deepfake-based fraud, and other cyberattacks.The contents of this book are appropriate for a wide range of readers from general readers to industry experts and scientists. Because it bridges the gap between generative AI and cybersecurity, experts from both fields will benefit from the information presented within. Students with a background in either area will also benefit from the approach that leads from general to specific applications.
R 7,579.25
Systems Engineering and Artificial Intelligence
This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams—where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.
R 5,936.95
R 2,748.00
Artificial Intelligence and Machine Learning Algorithms for Engineering Applications
This book comprehensively covers core algorithms and techniques used in artificial intelligence (AI) and machine learning (ML) for engineering applications. It further explores the use of AI in civil and structural engineering, quality control, and product design.Features:Presents autonomous robots using onboard computing and artificial intelligence (AI) algorithms to process the data from their sensors and make real-time decisionsDiscusses nature-based optimization-based computing techniques to enhance the computational speed for solving engineering problemsProvides conceptual and practical knowledge about the design of modern computation techniques with advanced tools and methodologiesHighlights the importance of using smart techniques including AI and ML in product design and developmentCovers time series analysis and forecasting in engineering, robotic process automation, and autonomous robots in manufacturingThe text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, manufacturing engineering, and environmental engineering.
R 8,248.58
R 323.00
Practical MLflow for Generative AI on Databricks
Bridge the gap between cutting-edge research and the practical operationalization of generative AI. This handy guide demystifies the complexities of managing GenAI applications using leading open source platform MLflow on Databricks.What sets this book apart is its focus on the requirements of managing and deploying GenAI applications. Authors Nuwan Ganganath, Julie Nguyen, and Chang Shi Lim—seasoned ML and AI specialists from Databricks—take you through each stage of the development of an agentic chatbot, sharing best practices, innovative techniques, and common challenges along the way. By combining deep technical insights with interactive exercises and actionable real-world code examples, they ensure that you're equipped to implement robust GenAI applications in modern enterprise environments.Understand MLflow fundamentals, including core components and the tool's application to GenAI on the Databricks platformBuild, track, and manage GenAI applications using MLflow, from prompts to the overall agentic chainOptimize and evaluate GenAI applications through a combination of automated LLM-assisted judges and human-in-the-loop reviewDeploy production-ready GenAI applications, leveraging Databricks' scalable infrastructure and monitoring capability
R 1,978.00
Intelligent Data Engineering and Automated Learning – IDEAL 2025
This two-volume set, LNCS 16238 and LNCS 16239, constitutes the proceedings of the 26th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2025, which was held in Jaén, Spain, during November 13-15, 2025. The 95 full papers and 12 short papers were carefully reviewed and selected from 146 submissions. The core themes of IDEAL 2025 included Trustworthy Artificial Intelligence and Generative AI, Aenetic AI, LLMs, Federated Learning, Machine Learning & Deep Learning for Real-World Applications, Data Mining and Pattern Recognition, Cybersecurity, Information Retrieval and Management, and Hybrid Intelligent Systems and Agents.
R 3,554.48
R 758.00
R 367.00
Generative AI
Generative AI (GenAI) is the hottest new area of AI, accelerating innovations affecting all industries and showcasing AI’s ability to present human-like language capabilities with large language models (LLMs). This book builds a solid foundation for the technology underlying GenAI Models, LLM, and foundation and reasoning models for the No-Code audience by explaining the models' workings in simple English. It then takes the reader on a journey to find out where there are gaps to innovate. Each chapter outlines the state of research in each topic and invites learners to build on this research to think about ethical implications and balance it with innovation to benefit everyone. The author covers the technological, product, and societal impact of Generative AI to give a comprehensive guide for this important technology. This book will help the data scientist, product manager, and business leader alike because it covers the API economy and critical industries impacted and offers a framework to think about automation and jobs impacted and what competencies are needed to excel in GenAI and offers an in-depth guide to build GenAI products and applications.
R 5,890.24
Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices
The rapid advancement of generative artificial intelligence (AI) has brought about significant ethical challenges. As machines become more adept at creating human-like content, concerns about misuse, bias, privacy, and accountability have emerged. Without clear guidelines and regulations, there is a risk of unethical use, such as creating deepfake videos or disseminating misinformation, which could have severe societal consequences. Additionally, questions about intellectual property rights and the ownership of AI-generated creations still need to be solved, further complicating the ethical landscape. The book, Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices , comprehensively solves these ethical challenges. By providing insights into the historical development and key milestones of Generative AI, the book lays a foundation for understanding its complex ethical implications. It examines existing ethical frameworks and proposes new ones tailored to AI's unique characteristics, helping readers apply traditional ethics to AI development and deployment. The book equips readers with the knowledge and tools needed to address these ethical considerations in AI development through in-depth discussions on bias, fairness, privacy, and security. It also explores the role of education in fostering responsible AI practices. It offers practical guidelines for ethical decision-making throughout the AI lifecycle. By promoting ethical awareness and providing actionable solutions, this book empowers readers to navigate the moral challenges of Generative AI, ensuring its responsible and beneficial use for society.
R 8,122.59
R 1,008.00
Introduction to Artificial Intelligence in Automotive Engineering
This book serves as a practical and timely guide to understanding how artificial intelligence can be applied and leveraged in automotive engineering. It demystifies complex methods of applying artificial intelligence and provides readers with the tools to creatively and immediately apply them to their own engineering challenges, transforming information into knowledge.Drawing on the authors' teaching experience, the book takes a practical approach to applying artificial intelligence tools - such as regression, classification, clustering, deep learning and reinforcement learning- to real-world engineering problems. Through clear explanations and step-by-step algorithmic structures, readers are introduced to the fundamental concepts of artificial intelligence and their practical application by building AI models using automotive data. Examples include predicting the energy consumption of electric vehicles under varying environmental and operating conditions, assessing battery degradation, analyzing brake system wear, and implementing intelligent control for thermal management (HVAC systems). The book shows how the application of artificial intelligence techniques and methods can optimize performance, increase safety, and stimulate innovation in the automotive sector.The book represents an essential guide for all those interested in exploring the application of artificial intelligence in automotive engineering (and beyond) and equally constitutes an effective support in the teaching process (courses, laboratories, projects) of applied artificial intelligence concepts.
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R 581.00
