Search results for "Python for Generative AI"
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R 763.00
Generative AI-Powered Assistant for Developers
Leverage Amazon Q Developer to boost productivity and maximize efficiency by accelerating software development life cycle tasksKey FeaturesFirst book on the market to thoroughly explore all of Amazon Q Developer’s featuresGain an understanding of Amazon Q Developer's capabilities across the software development life cycle through real-world examplesBuild apps with Amazon Q Developer by auto-generating code in various languages within supported IDEsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMany developers face the challenge of managing repetitive tasks and maintaining productivity. This book will help you tackle both these challenges with Amazon Q Developer, a generative AI-powered assistant designed to optimize coding and streamline workflows.This book takes you through the setup and customization of Amazon Q Developer, demonstrating how to leverage its capabilities for auto-code generation, code explanation, and transformation across multiple IDEs and programming languages. You'll learn to use Amazon Q Developer to enhance coding experiences, generate accurate code references, and ensure security by scanning for vulnerabilities. The book also shows you how to use Amazon Q Developer for AWS-related tasks, including solution building, applying architecture best practices, and troubleshooting errors. Each chapter provides practical insights and step-by-step guidance to help you fully integrate this powerful tool into your development process. You’ll get to grips with effortless code implementation, explanation, transformation, and documentation, helping you create applications faster and improve your development experience.By the end of this book, you’ll have mastered Amazon Q Developer to accelerate your software development lifecycle, improve code quality, and build applications faster and more efficiently.What you will learnUnderstand the importance of generative AI-powered assistants in developers' daily workEnable Amazon Q Developer for IDEs and with AWS services to leverage code suggestionsCustomize Amazon Q Developer to align with organizational coding standardsUtilize Amazon Q Developer for code explanation, transformation, and feature developmentUnderstand code references and scan for code security issues using Amazon Q DeveloperAccelerate the development of solutions and troubleshooting errors on AWSWho this book is forThis book is for coders, software developers, application builders, data engineers, and technical resources using AWS services looking to leverage Amazon Q Developer's features to enhance productivity and accelerate business outcomes. Basic coding skills are needed to understand the concepts covered in this book.
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Generative Artificial Intelligence in Healthcare
Generative artificial intelligence (AI) is a transformative force in smart healthcare. It can produce contents virtually indistinguishable from human-created material, with the power to redefine healthcare and revolutionize how medical science interacts with technology. This book presents the potential applications and benefits of generative AI in healthcare and discusses its execution challenges and ethical aspects.Generative Artificial Intelligence in Healthcare: Current Practices and Future Development starts by reviewing the past and then discussing the present of generative AI-based systems and the potential challenges the future might bring. It then highlights the integration of generative AI with IoT and blockchain technologies along with offering case studies. The book explores how to integrate augmented and virtual reality into generative AI-based healthcare and covers the development of an effective machine algorithm for generative AI-based healthcare, as well as the design and implementation of generative adversarial networks (GANs) in healthcare systems.Discussions about data security and ergonomic design for healthcare products are also included in the book. This book will provide a platform for the past, present, and future of generative AI and will help researchers and healthcare practitioners generate more robust solutions.
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AI in Popular Culture
This book examines the transformative impact of generative AI on cultural production, with a particular focus on how AI technologies like ChatGPT are reshaping the creation of popular culture.Through a comprehensive analysis of both Global North and South perspectives, the book offers critical insights into AI governance, ethical considerations, and the future of cultural production in an increasingly AI-integrated creative landscape. Tracing the evolution of AI in cultural industries, from its early representations in films to its current active role in content creation across various media, including film, television, music, and animation, the book explores how AI has shifted from being merely depicted in cultural works to becoming an integral tool in the creative process, from pre-production to post-production stages. It critically analyzes three core concepts—creativity, control, and credentials (3Cs)—in the context of AI-driven cultural production, putting focus on the examination of "precarious creativity," the tension between human creative expression and AI-generated content. The work addresses crucial concerns about labor rights, job security, and creative control in the cultural industries.This book will interest graduate students and researchers in media studies, cultural studies, anthropology, globalization studies, sociology, and science and technology studies (STS), as well as interested policymakers and practitioners interested in AI's impact on the creative industries.
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Using Generative AI in Historical Practice
'Using Generative AI in Historical Practice' argues that generative models are reshaping historical scholarship. Rejecting medium - and long -term speculation, it focuses on near-term practice: how historians can use AI now to augment their research through context-aware dialogue, semantic search, network visualization, multimodal source analysis, and code-assisted workflows. It details methods for context management, task design, and response structure, while warning against cognitive offloading and model bias. While it offers a variety of novel methodologies, the book insists on the indispensability of human agency and taste. Case studies range from Augustine of Hippo to early cinematography, demonstrating the possibilities and limits of generative AI. It concludes with a call to historians to engage with the technology critically and productively, reimagining AI-assisted scholarship without surrendering disciplinary standards and aims.
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DeepSeek in Action
From fundamental concepts to advanced implementations, this book thoroughly explores the DeepSeek-V3 model, focusing on its Transformer-based architecture, technological innovations, and applications.The book begins with a thorough examination of theoretical foundations, including self-attention, positional encoding, the Mixture of Experts mechanism, and distributed training strategies. It then explores DeepSeek-V3’s technical advancements, including sparse attention mechanisms, FP8 mixed-precision training, and hierarchical load balancing, which optimize memory and energy efficiency. Through case studies and API integration techniques, the model's high-performance capabilities in text generation, mathematical reasoning, and code completion are examined. The book highlights DeepSeek’s open platform and covers secure API authentication, concurrency strategies, and real-time data processing for scalable AI applications. Additionally, the book addresses industry applications, such as chat client development, utilizing DeepSeek’s context caching and callback functions for automation and predictive maintenance.This book is aimed primarily at AI researchers and developers working on large-scale AI models. It is an invaluable resource for professionals seeking to understand the theoretical underpinnings and practical implementation of advanced AI systems, particularly those interested in efficient, scalable applications.
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Deep Generative Models
This book constitutes the refereed proceedings of the Second MICCAI Workshop on Deep Generative Models, DG4MICCAI 2022, held in conjunction with MICCAI 2022, in September 2022. The workshops took place in Singapore. DG4MICCAI 2022 accepted 12 papers from the 15 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community.
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AI-Ready Data Blueprints
Companies innovating with generative AI understand that having the right data foundation is critical for success and profitability. To best position themselves for long-term success, organizations must prioritize investments in data and AI governance. AI-Ready Data Blueprints is your map to connecting data strategy, GenAI, and ethical practices to build and scale truly effective solutions. Taking a comprehensive, cloud-agnostic approach focused on real-world business challenges, seasoned data and AI experts Navnit Shukla, Kien Pham, Srikanth Sopirala, and Harsha Tadiparthi share actionable insights to guide you in designing and implementing effective data-centric GenAI systems. Whether you're new to GenAI or are already focusing on optimizing it for accuracy, speed, or both, the principles shared in this book will empower you to excel in all your AI endeavors. Identify the key elements of a solid data foundation for generative AIApply data governance and orchestration techniques to ensure high data quality, access control, and proper data lineage for reliable AI systemsOptimize GenAI applications through prompt engineering, fine-tuning, and retrieval-augmented generationImplement security, compliance, and governance measures, including responsible AI practices, transparency, and more
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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.
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