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 Generative Infrastructure-as-Code by Ajit Singh English | November 12, 2025 | ISBN: N/A | ASIN: B0G1ZBR2T9 | 382 pages | EPUB | 1.66 Mb "Generative Infrastructure-as-Code" is a comprehensive guide designed to navigate the cutting-edge intersection of Generative AI and modern infrastructure management. It demystifies how Large Language Models (LLMs) and other AI techniques can be used to automate the creation, deployment, and maintenance of cloud infrastructure, transforming a complex, code-intensive process into an intuitive, prompt-driven one.  Generative Everything Where Innovation meets Imagination by Ajit Singh English | December 5, 2025 | ISBN: N/A | ASIN: B0G56KB4KS | 359 pages | EPUB | 1.58 Mb "Generative Everything: Where Innovation meets Imagination" is a comprehensive, practical, and forward-looking guide designed to navigate the dynamic landscape of Generative Artificial Intelligence. It serves as an essential textbook and practical handbook for undergraduate and postgraduate students, as well as a valuable resource for professionals and researchers in the field of computer science and AI.  Generative Artificial Intelligence in Healthcare (Artificial Intelligence in Smart Healthcare Systems) by Rajendra Kumar, Shankar Ramamoorthy, Vishal Jain English | July 28, 2025 | ISBN: 1032784849 | 346 pages | MOBI | 6.57 Mb 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 Algorithms: AI as an Inventor by Ajit Singh English | December 1, 2025 | ISBN: N/A | ASIN: B0G4L1TG8Q | 354 pages | EPUB | 2.28 Mb "Generative Algorithms : AI as an Inventor" is a comprehensive textbook designed to navigate the exciting and rapidly evolving field where artificial intelligence transitions from an executor of human-designed algorithms to a creator of novel ones. This book serves as both a theoretical guide and a practical handbook for undergraduate (B.Tech) and postgraduate (M.Tech) students in Computer Science, as well as for professionals and researchers in the field of AI.  Generative Agentic AI by Ajit Singh English | November 6, 2025 | ISBN: N/A | ASIN: B0G12LCR12 | 381 pages | EPUB | 1.79 Mb "Generative Agentic AI" is a comprehensive textbook and practical guide designed to navigate the exciting confluence of generative AI and autonomous agent technology. It systematically demystifies how we can empower Large Language Models (LLMs) and other foundation models to not only generate content but to actively reason, plan, and execute complex tasks in both digital and physical environments. This book bridges the gap between theoretical knowledge and practical implementation, making it an essential resource for the next generation of AI engineers and developers.  Generative AI with Python and PyTorch: Navigating the AI frontier with LLMs, Stable Diffusion, and next-gen AI applications English | March 28, 2025 | ASIN: B0D9QBYYBQ | 450 pages | EPUB (True) | 35.00 MB Master GenAI techniques to create images and text using variational autoencoders (VAEs), generative adversarial networks (GANs), LSTMs, and large language models (LLMs) Key Features Implement real-world applications of LLMs and generative AI Fine-tune models with PEFT and LoRA to speed up training Expand your LLM toolbox with Retrieval Augmented Generation (RAG) techniques, LangChain, and LlamaIndex Purchase of the print or Kindle book includes a free eBook in PDF format Book Description Become an expert in Generative AI through immersive, hands-on projects that leverage today's most powerful models for Natural Language Processing (NLP) and computer vision. Generative AI with Python and PyTorch is your end-to-end guide to creating advanced AI applications, made easy by Raghav Bali, a seasoned data scientist with multiple patents in AI, and Joseph Babcock, a PhD and machine learning expert. Through business-tested approaches, this book simplifies complex GenAI concepts, making learning both accessible and immediately applicable. From NLP to image generation, this second edition explores practical applications and the underlying theories that power these technologies. By integrating the latest advancements in LLMs, it prepares you to design and implement powerful AI systems that transform data into actionable intelligence. You'll build your versatile LLM toolkit by gaining expertise in GPT-4, LangChain, RLHF, LoRA, RAG, and more. You'll also explore deep learning techniques for image generation and apply styler transfer using GANs, before advancing to implement CLIP and diffusion models. Whether you're generating dynamic content or developing complex AI-driven solutions, this book equips you with everything you need to harness the full transformative power of Python and AI. What you will learn Grasp the core concepts behind large language models and their capabilities Craft effective prompts using chain-of-thought, ReAct, and prompt query language to guide LLMs toward your desired outputs Understand how attention and transformers have changed NLP Optimize your diffusion models by combining them with VAEs Build text generation pipelines based on LSTMs and LLMs Leverage the power of open-source LLMs, such as Llama and Mistral, for diverse applications Who this book is for This book is for data scientists, machine learning engineers, and software developers seeking practical skills in building generative AI systems. A basic understanding of math and statistics and experience with Python coding is required. Table of Contents Introduction to Generative AI: Drawing Data from Models Building Blocks of Deep Neural Networks The Rise of Methods for Text Generation NLP 2.0: Using Transformers to Generate Text LLM Foundations Open-Source LLMs Prompt Engineering LLM Toolbox LLM Optimization Techniques Emerging Applications in Generative AI Neural Networks Using VAEs Image Generation with GANs Style Transfer with GANs Deepfakes with GANs Diffusion Models and AI Art  Generative AI with Python: Build Image Generators, Chatbots, and Smart Apps English | 18 Dec. 2025 | ASIN: B0G8KSFTG7 | 342 pages | Epub | 339.25 KB Generative AI with Python is a practical, beginner-friendly guide for anyone who wants to move beyond AI theory and start building real, useful applications with confidence. This book takes you step by step into the world of generative artificial intelligence using Python, one of the most powerful and accessible programming languages today. You will learn how modern AI systems work, not just at a surface level, but in a way that helps you apply them to real problems. From generating images and text to building intelligent chatbots and smart assistants, the focus is always on hands-on learning and real-world use cases. You begin with clear foundations. The book explains core AI concepts, language models, and image generation in simple terms, making it suitable even if you are new to AI. As you progress, you move into practical development, using modern libraries and tools to generate images, customize styles, control outputs, and troubleshoot common issues. Every major concept is supported with working Python examples that you can run, modify, and build upon. A major strength of this book is how it connects individual skills into complete applications. You will learn how to create chatbots with memory, build document Q&A systems, design image generators with user interfaces, and combine vision and language models into smart multimodal apps. By the time you reach the later chapters, you will be developing end-to-end AI solutions that feel professional and production-ready. Beyond building apps, the book also prepares you for real opportunities. You will discover how to deploy and scale AI projects, manage costs, secure your applications, and turn your skills into freelance services, products, or business ideas. The final chapters guide you through portfolio building and staying relevant in the fast-changing AI industry. Written in a clear, conversational style, Generative AI with Python balances depth with simplicity. It avoids unnecessary jargon, focuses on what truly matters, and emphasizes learning by doing. Whether you are a student, developer, entrepreneur, or tech enthusiast, this book gives you the practical knowledge and confidence to build image generators, chatbots, and smart AI-powered applications that work in the real world. By the end of this book, you will not just understand generative AI. You will know how to use it, deploy it, and turn it into something valuable. Author: Luis Alexandra  Generative AI with LangChain for Beginners: Build Smart AI Agents, RAG Systems, and Real-World LLM Applications with Practical Python Tutorials English | 17 Dec. 2025 | ASIN: B0G7RTRVYG | 378 pages | Epub | 2.64 MB Generative AI with LangChain for Beginners: Build Smart AI Agents, RAG Systems, and Real-World LLM Applications with Practical Python Tutorials Overview This book is a practical, beginner-friendly guide to building real-world generative AI applications using LangChain and Python. It introduces you to the core ideas behind large language models and shows you how to move beyond simple prompts to create intelligent systems that reason, retrieve information, use tools, and operate reliably in production. Rather than focusing on theory alone, the book emphasizes hands-on learning and clear explanations that help you understand how modern AI applications actually work. You will learn how to design AI agents, build Retrieval-Augmented Generation systems, manage memory and tools, evaluate outputs, optimize performance, and deploy scalable applications. Each concept builds naturally on the previous one, making the learning journey smooth and confidence-building, even if you are new to LangChain or generative AI. The book starts by explaining how generative AI and LangChain fit together, then gradually guides you into building increasingly capable applications. You explore prompt design, chains, tools, and memory before moving into advanced topics like agent workflows, graph-based control, observability, evaluation, and cost optimization. Later chapters focus on deployment, security, monitoring, and real-world project walkthroughs that mirror production use cases. By the end, you are able to design, build, evaluate, and deploy complete AI systems with confidence using Python. Key Features of This Book This book focuses on practical, step-by-step learning using real examples that reflect how AI is used in professional environments. It covers AI agents, RAG pipelines, vector databases, observability with LangSmith, performance tuning, and deployment strategies. The content follows a clear progression from beginner concepts to production-ready applications, with an emphasis on clean design, reliability, and scalability. All tutorials are written in Python and aligned with modern LangChain workflows. Target Audience This book is ideal for beginners who want to enter generative AI development, Python developers looking to build LLM-powered applications, data engineers and software engineers exploring AI systems, and technical professionals who want a clear and practical introduction to LangChain, AI agents, and RAG systems. No advanced AI background is required, only basic Python knowledge and curiosity. If you want to stop experimenting with isolated prompts and start building real, reliable AI applications, this book is your guide. Dive in and learn how to design, build, and deploy intelligent generative AI systems with LangChain and Python one practical step at a time.  Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph English | 23 May 2025 | ASIN: B0DYK6PKWM | 713 pages | EPUB (True) | 6.36 MB Go beyond foundational LangChain documentation with detailed coverage of LangGraph interfaces, design patterns for building AI agents, and scalable architectures used in production-ideal for Python developers building GenAI applications Key Features Bridge the gap between prototype and production with robust LangGraph agent architectures Apply enterprise-grade practices for testing, observability, and monitoring Build specialized agents for software development and data analysis Purchase of the print or Kindle book includes a free PDF eBook Book Description This second edition tackles the biggest challenge facing companies in AI today: moving from prototypes to production. Fully updated to reflect the latest developments in the LangChain ecosystem, it captures how modern AI systems are developed, deployed, and scaled in enterprise environments. This edition places a strong focus on multi-agent architectures, robust LangGraph workflows, and advanced retrieval-augmented generation (RAG) pipelines. You'll explore design patterns for building agentic systems, with practical implementations of multi-agent setups for complex tasks. The book guides you through reasoning techniques such as Tree-of -Thoughts, structured generation, and agent handoffs-complete with error handling examples. Expanded chapters on testing, evaluation, and deployment address the demands of modern LLM applications, showing you how to design secure, compliant AI systems with built-in safeguards and responsible development principles. This edition also expands RAG coverage with guidance on hybrid search, re-ranking, and fact-checking pipelines to enhance output accuracy. Whether you're extending existing workflows or architecting multi-agent systems from scratch, this book provides the technical depth and practical instruction needed to design LLM applications ready for success in production environments. What you will learn Design and implement multi-agent systems using LangGraph Implement testing strategies that identify issues before deployment Deploy observability and monitoring solutions for production environments Build agentic RAG systems with re-ranking capabilities Architect scalable, production-ready AI agents using LangGraph and MCP Work with the latest LLMs and providers like Google Gemini, Anthropic, Mistral, DeepSeek, and OpenAI's o3-mini Design secure, compliant AI systems aligned with modern ethical practices Who this book is for This book is for developers, researchers, and anyone looking to learn more about LangChain and LangGraph. With a strong emphasis on enterprise deployment patterns, it's especially valuable for teams implementing LLM solutions at scale. While the first edition focused on individual developers, this updated edition expands its reach to support engineering teams and decision-makers working on enterprise-scale LLM strategies. A basic understanding of Python is required, and familiarity with machine learning will help you get the most out of this book. Table of Contents The Rise of Generative AI: From Language Models to Agents First Steps with LangChain Building Workflows with LangGraph Building Intelligent RAG Systems with LangChain Building Intelligent Agents Advanced Applications and Multi-Agent Systems Software Development and Data Analysis Agents Evaluation and Testing Observability and Production Deployment The Future of LLM Applications  Generative AI on Google Cloud with LangChain: Design scalable generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud by Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei English | December 20, 2024 | ISBN: 1835889336 | 474 pages | EPUB | 10 Mb Turn challenges into opportunities by learning advanced techniques for text generation, summarization, and question answering using LangChain and Google Cloud tools |
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