mastering generative software development de vemula anand (16 resultados)

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Paperback. Condición: new. Paperback. Mastering Generative AI Software Development equips you to harness the power of generative models, a revolutionary technology capable of creating entirely new and original content.Part 1 establishes a solid foundation. You'll explore the core concepts of generative models, contrasting them with traditional machine learning approaches. We'll delve into the exciting applications of generative AI, from creative content generation like writing and music composition to scientific breakthroughs in drug discovery and material science. The section concludes by discussing both the benefits and challenges associated with this powerful technology.Part 2 guides you through the practical steps of building generative AI systems. We'll tackle data preparation, a crucial stage for ensuring high-quality model training. You'll learn about different data cleaning and augmentation techniques to optimize your data for generative models. Moving on, we'll explore various generative model architectures like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). The section delves into the training process, equipping you with the knowledge to choose appropriate loss functions and optimizers for optimal model performance. We'll also explore techniques for monitoring and debugging the training process to ensure successful model development.Part 3 showcases the vast potential of generative AI software across diverse industries. We'll explore how generative models are revolutionizing creative fields, enabling artists and writers to generate new content and explore innovative avenues. Beyond the realm of creativity, we'll delve into the transformative role of generative AI in scientific research, accelerating drug discovery and material design processes. The section concludes by exploring additional applications like data augmentation and natural language processing tasks such as machine translation and chatbot development.Part 4 paves the way for the future. We'll discuss the ethical considerations surrounding generative AI development, particularly the potential for bias and the misuse of realistic content generation. The section concludes by exploring cutting-edge advancements like explainable generative models and the ever-expanding real-world applications of this technology.By the end of this comprehensive guide, you'll possess a thorough understanding of generative AI software development, empowering you to participate in shaping the future of this rapidly evolving field. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condición: new. Paperback. **Mastering Generative AI in the Software Development Life Cycle** explores the transformative potential of generative AI in modern software development. This comprehensive guide walks readers through integrating AI technologies across each phase of the Software Development Life Cycle (SDLC), from requirements gathering and system design to implementation, testing, deployment, and maintenance. The book begins with an overview of generative AI, explaining its core concepts, historical development, and diverse applications. It underscores the importance of the SDLC, contrasting traditional and agile methodologies, and addressing contemporary challenges in software development. In the system design phase, readers learn how AI can automate architectural design, create rapid prototypes, and optimize resource allocation. The implementation chapter highlights AI-assisted code generation, presenting best practices for ensuring the quality and maintainability of AI-generated code. Version control and collaboration tools are also discussed to streamline the development process. Testing is revolutionized through AI-driven automated test case generation, bug detection, and continuous integration and deployment (CI/CD). Real-world examples illustrate how AI can enhance efficiency and accuracy in these critical activities. The deployment chapter delves into AI for deployment optimization, including predictive analysis, automated rollbacks, and resource management. It also covers AI-powered monitoring and maintenance, with techniques for anomaly detection, predictive maintenance, and automated scaling. Maintenance and evolution are addressed with a focus on predictive maintenance using AI, adapting AI models to changing requirements, and exploring future trends like self-healing systems and advanced predictive analytics. Ethical and legal considerations, such as bias mitigation, transparency, accountability, and compliance with regulations like GDPR and HIPAA, are thoroughly examined. Industry case studies demonstrate AI's impact on various sectors, including finance, healthcare, and e-commerce. These examples show how AI enhances fraud detection, disease prediction, personalized recommendations, and more. The book also provides an overview of essential AI tools and technologies, offering guidance on integrating them into SDLC pipelines. It concludes with insights into emerging trends and the future of AI in software development, preparing readers for the evolving landscape of AI-driven development. **Mastering Generative AI in the Software Development Life Cycle** is an essential resource for developers, engineers, and tech enthusiasts aiming to harness AI's power to innovate and optimize their software development processes. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condición: new. Paperback. Mastering Generative AI Software Development equips you to harness the power of generative models, a revolutionary technology capable of creating entirely new and original content.Part 1 establishes a solid foundation. You'll explore the core concepts of generative models, contrasting them with traditional machine learning approaches. We'll delve into the exciting applications of generative AI, from creative content generation like writing and music composition to scientific breakthroughs in drug discovery and material science. The section concludes by discussing both the benefits and challenges associated with this powerful technology.Part 2 guides you through the practical steps of building generative AI systems. We'll tackle data preparation, a crucial stage for ensuring high-quality model training. You'll learn about different data cleaning and augmentation techniques to optimize your data for generative models. Moving on, we'll explore various generative model architectures like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). The section delves into the training process, equipping you with the knowledge to choose appropriate loss functions and optimizers for optimal model performance. We'll also explore techniques for monitoring and debugging the training process to ensure successful model development.Part 3 showcases the vast potential of generative AI software across diverse industries. We'll explore how generative models are revolutionizing creative fields, enabling artists and writers to generate new content and explore innovative avenues. Beyond the realm of creativity, we'll delve into the transformative role of generative AI in scientific research, accelerating drug discovery and material design processes. The section concludes by exploring additional applications like data augmentation and natural language processing tasks such as machine translation and chatbot development.Part 4 paves the way for the future. We'll discuss the ethical considerations surrounding generative AI development, particularly the potential for bias and the misuse of realistic content generation. The section concludes by exploring cutting-edge advancements like explainable generative models and the ever-expanding real-world applications of this technology.By the end of this comprehensive guide, you'll possess a thorough understanding of generative AI software development, empowering you to participate in shaping the future of this rapidly evolving field. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condición: new. Paperback. **Mastering Generative AI in the Software Development Life Cycle** explores the transformative potential of generative AI in modern software development. This comprehensive guide walks readers through integrating AI technologies across each phase of the Software Development Life Cycle (SDLC), from requirements gathering and system design to implementation, testing, deployment, and maintenance. The book begins with an overview of generative AI, explaining its core concepts, historical development, and diverse applications. It underscores the importance of the SDLC, contrasting traditional and agile methodologies, and addressing contemporary challenges in software development. In the system design phase, readers learn how AI can automate architectural design, create rapid prototypes, and optimize resource allocation. The implementation chapter highlights AI-assisted code generation, presenting best practices for ensuring the quality and maintainability of AI-generated code. Version control and collaboration tools are also discussed to streamline the development process. Testing is revolutionized through AI-driven automated test case generation, bug detection, and continuous integration and deployment (CI/CD). Real-world examples illustrate how AI can enhance efficiency and accuracy in these critical activities. The deployment chapter delves into AI for deployment optimization, including predictive analysis, automated rollbacks, and resource management. It also covers AI-powered monitoring and maintenance, with techniques for anomaly detection, predictive maintenance, and automated scaling. Maintenance and evolution are addressed with a focus on predictive maintenance using AI, adapting AI models to changing requirements, and exploring future trends like self-healing systems and advanced predictive analytics. Ethical and legal considerations, such as bias mitigation, transparency, accountability, and compliance with regulations like GDPR and HIPAA, are thoroughly examined. Industry case studies demonstrate AI's impact on various sectors, including finance, healthcare, and e-commerce. These examples show how AI enhances fraud detection, disease prediction, personalized recommendations, and more. The book also provides an overview of essential AI tools and technologies, offering guidance on integrating them into SDLC pipelines. It concludes with insights into emerging trends and the future of AI in software development, preparing readers for the evolving landscape of AI-driven development. **Mastering Generative AI in the Software Development Life Cycle** is an essential resource for developers, engineers, and tech enthusiasts aiming to harness AI's power to innovate and optimize their software development processes. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condición: New. Print on Demand.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condición: New. Print on Demand.