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Generative AI for Web Development
Explore the world of Generative AI and understand why it matters. This book is divided into two parts, introducing tools such as ChatGPT, DALL-E, and will show you how to use them to build AI-powered web apps.The first part of the book describes Generative AI and covers the essential models and APIs from OpenAI. Legal, ethical, and security considerations are discussed to help you decide whether it is an appropriate tool for your projects. You’ll then review ChatGPT and see how to use it effectively for generating code. This is followed by a review of best practices, and tips and techniques for getting around the limitations of ChatGPT and other OpenAI APIs.The second part of the book provides practical guide to building a series of web apps with Next.js that showcase how to use the OpenAI APIs. For example, you’ll learn how to build a Story/Poetry generator, a language learning app, and a blog site with a custom Chatbot widget. The code for the web apps is generated using ChatGPT.When done with this book, you’ll have a clear understanding of Generative AI and be well on your way to building web applications powered by OpenAI APIs and Next.js.What You Will LearnAssess the legal, ethical, and security concerns with using Generative AI in web applications Review the latest APIs provided by OpenAI for generating text and imageUse ChatGPT to generate code for web projects, as well as tips and tricks to working around the limitations.Who This Book Is ForExperienced web developers and software engineers who know their way around HTML, CSS, and JavaScript, but have limited or no experience using Generative AI to build web applications.
R 1,368.00
Gen AI-assisted Agile Course, Project-Based Teaching and Learning
This title represents an essential resource for understanding the evolving landscape of AI-augmented pedagogy, examining the transformative effects of generative artificial intelligence (GenAI) on education through the lens of agile course design and project-based learning.Through a detailed analysis of diverse empirical case studies from eight countries between 2015 and 2024, the authors effectively illustrate the dual impact of GenAI on education, academic integrity, and teacher autonomy. They demonstrate how GenAI can enhance personalized STEM education and STREAM (Science, Technology, Reading and Writing, Engineering, Arts and Mathematics) instruction, as well as project-based learning, while simultaneously presenting significant challenges. They provide a nuanced assessment of the opportunities and disruptions introduced by GenAI and offer concrete pedagogical strategies for teaching practitioners.This book serves as a vital reference for scholars in GenAI, educational technology and curriculum, and instruction. It also provides practical, ready-to-implement pedagogical approaches for pre-service teachers in higher education and primary and secondary schools.
R 9,298.36
R 367.00
Generative AI in R
Leverage Generative AI within the R programming environment and prepare for future directions and how new innovations can be applied in the R ecosystem. This pioneering book is designed to bridge the gap between the advanced realms of Generative AI and the practical, statistical computing power of R. You'll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. You'll then dive into the practicalities of implementing generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) in R. See how R, most known for its statistical analysis, can also be used for creative synthetic data, improving model robustness, and generating innovative insights from data. Additionally, this book addresses the demand for ethical AI by emphasizing the use of synthetic data to tackle privacy and data scarcity issues--concerns particularly relevant in healthcare, finance, and social research. We are at a pivotal moment in the evolution of AI and data science. With AI's growing importance, the book's focus on R makes advanced techniques more accessible, promoting ethical and innovative data science practice, preparing readers for upcoming trends. What You Will Learn Grasp the core concepts of Generative AI and its significance in the broader AI landscape. Implement various generative models in R, such as GANS and VAEs. Generate high-quality synthetic data. Apply advanced techniques for improving efficiency and effectiveness of models for different applications. Understand Gen AI ethical considerations. Who This Book Is For Data scientists and statisticians with intermediate R programming skills who want to expand into Generative AI for data analysis and problem-solving. AI enthusiasts and data analysts looking to apply Generative AI techniques in R to enhance their analytical capabilities.
R 912.00
R 886.00
AI-Generated Image and Video Synthesis
Technical depth and ethical frameworks for AI visual media synthesis Generative AI models for visual media are transforming virtual reality and biomedical imaging while raising urgent questions about deepfakes and misinformation. AI-Generated Image and Video Synthesis addresses both dimensions. A team of researchers provide algorithmic foundations alongside detection strategies, authentication methods, and regulatory analysis. Coverage spans text-to-image generation, image-to-image translation, video synthesis, neural rendering, and 3D-aware generation. The book examines AI applications in CT, MRI synthetic data augmentation, and virtual staining for biomedical contexts. Case studies explore AI-assisted filmmaking, music videos, and style transfer. A dedicated chapter forecasts emerging trends including diffusion-transformer hybrids and autonomous generative agents. Readers will also find: Comparative analyses of generative models including GANs, diffusion models, and transformers with implementation guidance and code repositories for hands-on experimentationDeepfake detection strategies and digital content authentication techniques addressing misinformation, intellectual property rights, and emerging regulatory frameworks worldwideIndustry case studies demonstrating real-world deployments in creative industries, surveillance systems, education, and cultural preservation applicationsBiomedical imaging applications covering synthetic data generation for CT and MRI, virtual staining techniques, and data augmentation strategiesPractical toolkits and online resources supporting implementation and evaluation of AI synthesis techniques across professional and academic contexts Designed for AI researchers, computer vision engineers, and graduate students studying deep learning and image processing, this book connects theoretical principles with practical deployment. The combination of technical depth, application coverage, and ethical analysis makes it a comprehensive resource for professionals navigating AI-generated visual media.
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Generative AI and Education
This volume addresses the gap in knowledge around generative AI and its applications in education. It draws on the recent history of technological innovation and digital pedagogies, locating generative AI in the contemporary discourse around education futures. It argues that a new hybrid model of education is emerging, requiring educational institutions to embed generative AI into course and programme design, delivery and assessment. It also proposes a shift from a focus on learning as output to learning as a process, and explores what that shift might look like. Grounded in educational theory, it offers actionable pedagogy-informed guidance on how to position AI as a collaborator in the construction of learning in a manner that is congruent with the values and aims of education. It offers advice based on evidence-based digital pedagogy, including frameworks for effective teaching and learning with generative AI, that enable educators and designers to put these ideas into practice.The book also explores the wider context informing this shift, connecting narratives from governments and industry leaders on the strategic importance of generative AI and lifelong learning, learning agility, and future skills that make the case for the integration of competency-based assessment into mainstream education. Finally, going beyond pedagogy and practice, it considers of some of the broader issues, including limitations and ethics, and the implications of integrating generative AI into institutional planning and design, and includes a sample roadmap for education leaders to start the process of integrating generative AI into their institutions.This work approaches the topic of generative AI from the vantage point of educators by addressing themes and concerns that will resonate with professionals in the sector.
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R 912.00
Computer Vision Projects with PyTorch
Design and develop end-to-end, production-grade computer vision projects for real-world industry problems. This book discusses computer vision algorithms and their applications using PyTorch.The book begins with the fundamentals of computer vision: convolutional neural nets, RESNET, YOLO, data augmentation, and other regularization techniques used in the industry. And then it gives you a quick overview of the PyTorch libraries used in the book. After that, it takes you through the implementation of image classification problems, object detection techniques, and transfer learning while training and running inference. The book covers image segmentation and an anomaly detection model. And it discusses the fundamentals of video processing for computer vision tasks putting images into videos. The book concludes with an explanation of the complete model building process for deep learning frameworks using optimized techniques with highlights on model AI explainability.After reading this book, you will be able to build your own computer vision projects using transfer learning and PyTorch.What You Will LearnSolve problems in computer vision with PyTorch.Implement transfer learning and perform image classification, object detection, image segmentation, and other computer vision applicationsDesign and develop production-grade computer vision projects for real-world industry problemsInterpret computer vision models and solve business problemsWho This Book Is ForData scientists and machine learning engineers interested in building computer vision projects and solving business problems
R 1,482.00
Communication Skills for Generative AI
Communication Skills for Generative AI: A Practical Guide for Humans is the first comprehensive book to treat communication with generative AI as a distinct human competence—analogous to digital literacy, media literacy, or academic writing skills. Instead of framing the field through the narrow lens of “prompt engineering,” this book introduces a broader, deeper, and more natural paradigm: human–AI communication. It argues that as generative AI becomes embedded in daily life, professional work, research, education, and creative practices, humans must learn not merely to instruct AI systems but to communicate with them effectively, collaboratively, and safely. The book covers the foundations, principles, techniques, and future directions of communicating with modern AI systems. It begins by explaining why the rise of generative AI requires a new set of human capabilities, then outlines the psychological, linguistic, cognitive, and interactional mechanisms that shape human–AI dialogue. It provides a systematic structure of principles (clarity, intent, iteration, cognitive alignment, ethical responsibility) and practical techniques (contextual communication, constraint-based approaches, multimodality, iterative refinement, tone and persona control). The book also examines pitfalls and sources of misunderstanding—such as ambiguity, hallucination, overtrust, and guardrails—and offers strategies for detecting and resolving them. A central contribution of the book is its treatment of collaborative and co-creative communication, where AI is understood not as a passive tool but as an active cognitive partner capable of supporting reasoning, generating ideas, and co-creating text, visuals, and solutions. Another unique perspective is the chapter on metacommunication, which teaches readers how to talk about the communication process itself— expressing preferences, adjusting strategies, and aligning expectations during the dialogue. The book concludes with a forward-looking exploration of the future of AI communication: post-prompting paradigms, persistent personal assistants, intuitive and emotional interfaces, hybrid reasoning models, and the evolving competencies humans will need as AI becomes increasingly autonomous and embedded. This book relates to existing literature on prompt engineering, human–computer interaction, and AI literacy but significantly expands beyond them. While traditional books focus on crafting prompts or operating tools, this work builds a conceptual and methodological foundation for treating AI as a communicative partner. It introduces a unified framework for understanding interaction across text, multimodal interfaces, and emerging real-time systems. This broader perspective positions the book as a pioneering contribution that addresses an urgent gap in current academic, professional, and educational discourse.
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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 1,955.66
Data Lakehouse Revolution
We are racing toward a new kind of AI--faster, smarter, and more connected than ever. At the heart of it is the Data Lakehouse, and Databricks is the engine powering the transformation. Whether you're a data scientist training models, an engineer scaling pipelines, or an architect modernizing your stack, this book gives you what you need to stay ahead. Inside, you'll understand how to unlock the full potential of Machine Learning and Generative AI (GenAI) using Databricks--no fluff, just real tools, real strategies, and real results. From MLFlow and AutoML to Unity Catalog, Retrieval Augment Generation (RAG), and Vector Search, you'll get a complete blueprint for building intelligent systems that actually work in production. With step-by-step labs, industry case studies, and expert tips from someone who's lived through the entire evolution of enterprise AI, this book is your guide to mastering what's next. If you're serious regarding building AI that matters, this is where your journey begins. What You'll Learn Build full-stack ML and GenAI solutions on Databricks Train and track models with MLFlow, AutoML, and tuning strategies Secure and govern data with Unity Catalog Apply explainable, ethical AI techniques Deploy and monitor ML models in real-world pipelines Use RAG and vector search to power GenAI applications Gain confidence with hands-on labs and real enterprise use cases Who This Book Is For Azure administrators, data architects, and data engineers
R 1,368.00
R 1,161.00
Empowering the Public Sector with Generative AI
This is your guide book to Generative AI (GenAI) and its application in addressing real-world challenges within the public sector. The book addresses a range of topics from GenAI concepts and strategy to public sector use cases, architecture patterns, and implementation best practices. With a general background in technology and the public sector, you will be able to understand the concepts in this book.The book will help you develop a deeper understanding of GenAI and learn how GenAI differs from traditional AI. You will explore best practices such as prompt engineering, and fine-tuning, and architectural patterns such as Retrieval Augmented Generation (RAG). And you will discover specific nuances, considerations, and strategies for implementation in a public sector organization. You will understand how to apply these concepts in a public sector setting and address industry-specific challenges and problems by studying a variety of use cases included in the book in the areas of content generation, chatbots, summarization, and program management. What You Will LearnGenAI concepts and how GenAI differs from traditional AI/ML Prompt engineering, fine-tuning, RAG, and customizing foundation modelsStrategy, methodologies, and frameworks for the public sectorPublic sector use cases in the areas of content generation, summarization, and chatbots, plus program management, analytics, business intelligence, and reportingArchitecture and design patterns Implementation, operations, and maintenance of GenAI applications Who This Book Is ForTechnology and business leaders in the public sector who are new to AI/ML and are keen on exploring and harnessing the potential of Generative AI in their respective organizations.
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R 550.00
Microlearning with GenAI
This Element explores the innovative integration of microlearning and generative artificial intelligence (GenAI) in second-language education. Designed for language teachers, teacher trainers, and future educators, it offers research-informed insights and actionable strategies for designing learner-centred, technology-enhanced instruction. The Element introduces the evolution and applications of GenAI in language learning, examines its synergy with microlearning, and presents pedagogical frameworks rooted in SLA theory, cognitive load theory, and multimodal learning. Practical guidance is provided for designing, implementing, and evaluating AI-assisted microlearning tasks, focusing on interactivity, accessibility, and ethical use. The Element also explores GenAI's role in teacher professional development and considers future trends shaping language education. While celebrating the transformative potential of GenAI, it critically engages with the challenges and limitations of emerging technologies. Through a balanced blend of theory and practice, this Element equips educators with the knowledge and tools to navigate and harness the evolving AI-enhanced language learning landscape.
R 2,808.44
R 1,140.00
R 805.00
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
R 611.00
Art and Ethics of Generative AI
Generative AI technologies are reshaping the way we create, communicate, and compute, presenting both unprecedented opportunities and profound challenges. As these systems increasingly influence decisions that shape our lives, it becomes clear that performance metrics alone cannot define their success. A deeper understanding of the intersection between technical innovation and human values is essential to navigate this transformative era.The Art and Ethics of Generative AI: Fairness, Transparency, and Human Values provides a balanced exploration of generative AI, combining technical insights with ethical considerations. It explains generative model architectures and learning paradigms in an accessible way, while addressing critical issues such as algorithmic bias, explainability challenges, and emerging regulatory approaches. Practical frameworks for responsible AI development are offered, alongside multidisciplinary perspectives that bridge technical and humanistic viewpoints. Abstract concepts are brought to life through practical illustrations, demonstrating how ethical considerations play out in real-world AI applications.Designed for a wide audience, the book serves AI practitioners seeking actionable guidance for building responsible systems, researchers exploring nuanced ethical dimensions, educators and students looking for comprehensive learning materials, and policymakers needing governance insights. It is an essential resource for anyone engaged in the rapidly evolving AI ecosystem.
R 5,165.00
Generative AI and Generative AI of Things for Sustainable Smart Cities
This pioneering book invites readers on a compelling journey into Generative Artificial Intelligence (AI) and its groundbreaking convergence with AI of Things (AIoT), introducing GAIoT as a transformative frontier in urban computing and intelligence. GAIoT signals a paradigm shift towards more intelligent, self-learning, self-evolving, and context-aware systems—capable of generating adaptive, forward-looking solutions to the complex infrastructuraland environmental challenges confronting sustainable smart cities.With its combination of theoretical depth, applied innovation, and interdisciplinary scope, the book offers a comprehensive examination of deep generative models—namely Generative Adversarial Networks, Variational Autoencoders, Diffusion Models, Transformers, and hybrid architectures—and their applications in environmental sustainability, climate resilience, infrastructure optimization, dynamic decision-making, and data-driven urban management and planning. From synthetic data generation, data augmentation, and data imputation to predictive modeling and scenario simulation, GAIoT is driving the next wave of climate-responsive, environmentally conscious smart city innovation.What sets this book apart is its first-of-its-kind focus on GAIoT as a pathbreaking force in shaping the future of sustainable urban development. It delivers actionable insights, conceptual and operational frameworks, case studies, and policy guidance—equipping diverse stakeholders with the tools to build cities that not only respond to change but also anticipate and shape it. Targeting a broad and cross-disciplinary audience, the book shares state-of-the-art research, presents innovative solutions, and forecasts future trends in urban transformation. As both a seminal reference and a practical resource for researchers, technologists, practitioners, professionals, and policymakers, it provides essential guidance for those engaged in advancing the next frontier in urban computing and intelligence.
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Artificial Intelligence with Python
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more.Key FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook DescriptionArtificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications.This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data.Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques.What you will learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is forThe intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.
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R 1,130.00
