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Llms


Llms
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Llms And Generative Ai For Healthcare


Llms And Generative Ai For Healthcare
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Author : Kerrie Holley
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-08-20

Llms And Generative Ai For Healthcare written by Kerrie Holley and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-20 with Computers categories.


Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare. Authors Kerrie Holley, former Google healthcare professionals, guide you through the transformative potential of large language models (LLMs) and generative AI in healthcare. From personalized patient care and clinical decision support to drug discovery and public health applications, this comprehensive exploration covers real-world uses and future possibilities of LLMs and generative AI in healthcare. With this book, you will: Understand the promise and challenges of LLMs in healthcare Learn the inner workings of LLMs and generative AI Explore automation of healthcare use cases for improved operations and patient care using LLMs Dive into patient experiences and clinical decision-making using generative AI Review future applications in pharmaceutical R&D, public health, and genomics Understand ethical considerations and responsible development of LLMs in healthcare "The authors illustrate generative's impact on drug development, presenting real-world examples of its ability to accelerate processes and improve outcomes across the pharmaceutical industry."--Harsh Pandey, VP, Data Analytics & Business Insights, Medidata-Dassault Kerrie Holley is a retired Google tech executive, IBM Fellow, and VP/CTO at Cisco. Holley's extensive experience includes serving as the first Technology Fellow at United Health Group (UHG), Optum, where he focused on advancing and applying AI, deep learning, and natural language processing in healthcare. Manish Mathur brings over two decades of expertise at the crossroads of healthcare and technology. A former executive at Google and Johnson & Johnson, he now serves as an independent consultant and advisor. He guides payers, providers, and life sciences companies in crafting cutting-edge healthcare solutions.



Building Ai Agents With Llms Rag And Knowledge Graphs


Building Ai Agents With Llms Rag And Knowledge Graphs
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Author : Salvatore Raieli
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-07-11

Building Ai Agents With Llms Rag And Knowledge Graphs written by Salvatore Raieli and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Computers categories.


Master LLM fundamentals to advanced techniques like RAG, reinforcement learning, and knowledge graphs to build, deploy, and scale intelligent AI agents that reason, retrieve, and act autonomously Key Features Implement RAG and knowledge graphs for advanced problem-solving Leverage innovative approaches like LangChain to create real-world intelligent systems Integrate large language models, graph databases, and tool use for next-gen AI solutions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis AI agents book addresses the challenge of building AI that not only generates text but also grounds its responses in real data and takes action. Authored by AI specialists with deep expertise in drug discovery and systems optimization, this guide empowers you to leverage retrieval-augmented generation (RAG), knowledge graphs, and agent-based architectures to engineer truly intelligent behavior. By combining large language models (LLMs) with up-to-date information retrieval and structured knowledge, you'll create AI agents capable of deeper reasoning and more reliable problem-solving. Inside, you'll find a practical roadmap from concept to implementation. You’ll discover how to connect language models with external data via RAG pipelines for increasing factual accuracy and incorporate knowledge graphs for context-rich reasoning. The chapters will help you build and orchestrate autonomous agents that combine planning, tool use, and knowledge retrieval to achieve complex goals. Concrete Python examples built on popular libraries, along with real-world case studies, reinforce each concept and show you how these techniques come together. By the end of this book, you’ll be well-equipped to build intelligent AI agents that reason, retrieve, and interact dynamically, empowering you to deploy powerful AI solutions across industries.What you will learn Learn how LLMs work, their structure, uses, and limits, and design RAG pipelines to link them to external data Build and query knowledge graphs for structured context and factual grounding Develop AI agents that plan, reason, and use tools to complete tasks Integrate LLMs with external APIs and databases to incorporate live data Apply techniques to minimize hallucinations and ensure accurate outputs Orchestrate multiple agents to solve complex, multi-step problems Optimize prompts, memory, and context handling for long-running tasks Deploy and monitor AI agents in production environments Who this book is for If you are a data scientist or researcher who wants to learn how to create and deploy an AI agent to solve limitless tasks, this book is for you. To get the most out of this book, you should have basic knowledge of Python and Gen AI. This book is also excellent for experienced data scientists who want to explore state-of-the-art developments in LLM and LLM-based applications.



Building Llm Powered Applications


Building Llm Powered Applications
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Author : Valentina Alto
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-22

Building Llm Powered Applications written by Valentina Alto and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-22 with Computers categories.


Get hands-on with GPT 3.5, GPT 4, LangChain, Llama 2, Falcon LLM and more, to build LLM-powered sophisticated AI applications Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Embed LLMs into real-world applications Use LangChain to orchestrate LLMs and their components within applications Grasp basic and advanced techniques of prompt engineering Book DescriptionBuilding LLM Powered Applications delves into the fundamental concepts, cutting-edge technologies, and practical applications that LLMs offer, ultimately paving the way for the emergence of large foundation models (LFMs) that extend the boundaries of AI capabilities. The book begins with an in-depth introduction to LLMs. We then explore various mainstream architectural frameworks, including both proprietary models (GPT 3.5/4) and open-source models (Falcon LLM), and analyze their unique strengths and differences. Moving ahead, with a focus on the Python-based, lightweight framework called LangChain, we guide you through the process of creating intelligent agents capable of retrieving information from unstructured data and engaging with structured data using LLMs and powerful toolkits. Furthermore, the book ventures into the realm of LFMs, which transcend language modeling to encompass various AI tasks and modalities, such as vision and audio. Whether you are a seasoned AI expert or a newcomer to the field, this book is your roadmap to unlock the full potential of LLMs and forge a new era of intelligent machines.What you will learn Explore the core components of LLM architecture, including encoder-decoder blocks and embeddings Understand the unique features of LLMs like GPT-3.5/4, Llama 2, and Falcon LLM Use AI orchestrators like LangChain, with Streamlit for the frontend Get familiar with LLM components such as memory, prompts, and tools Learn how to use non-parametric knowledge and vector databases Understand the implications of LFMs for AI research and industry applications Customize your LLMs with fine tuning Learn about the ethical implications of LLM-powered applications Who this book is for Software engineers and data scientists who want hands-on guidance for applying LLMs to build applications. The book will also appeal to technical leaders, students, and researchers interested in applied LLM topics. We don’t assume previous experience with LLM specifically. But readers should have core ML/software engineering fundamentals to understand and apply the content.



Llm Development And Ai Ethics


Llm Development And Ai Ethics
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Author : Ambuj Agrawal
language : en
Publisher: BPB Publications
Release Date : 2025-03-23

Llm Development And Ai Ethics written by Ambuj Agrawal and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-23 with Computers categories.


DESCRIPTION The rapid evolution of AI, especially generative AI, presents both opportunities and critical challenges. This book addresses the urgent need for responsible AI development, focusing on safety, alignment, and robust governance. We explore how to navigate the complexities of AI, ensuring its benefits are harnessed while mitigating potential risks. This book will cover the foundational concepts of AI, from ML to the cutting-edge of large language models (LLMs) and prompt engineering. Each chapter provides key insights into AI safety initiatives, governance frameworks, and the practical development of secure AI applications. You will learn how to approach AI with an ethical mindset, understanding the importance of interpretability, risk management, and the societal implications of AI advancements, all the way to contemplating the future of artificial general intelligence (AGI). Upon completing this book, you will possess a comprehensive understanding of AI's current state and future trajectories. You will gain the knowledge to contribute to the responsible development and deployment of AI technologies, ready to engage in the crucial conversations shaping our AI-driven world. WHAT YOU WILL LEARN ● Create generative AI applications for text, music, image, and video generation. ● Develop ML models and LLMs from scratch. ● Work towards advancing the field of AI safety and alignment. ● Build AI applications with AI governance and security. ● Create AI governance frameworks for your organizations. ● Develop better prompts for generative AI models using the prompt engineering techniques mentioned in the book. ● Build AI agents for workflow automation. ● Understand the latest trend in generative AI research and the current progress towards AGI. WHO THIS BOOK IS FOR This book is intended for technologists, researchers, business leaders, and AI enthusiasts. Even people with no technical knowledge can use the techniques described in this book to create generative AI applications for a variety of use cases in their organizations. TABLE OF CONTENTS 1. Introduction to Artificial Intelligence 2. Introduction to AI Safety and Alignment 3. Introduction to Generative AI 4. Developing Large Language Models 5. Prompt Engineering and Its Impact on AI Safety 6. AI Governance in the Age of Generative AI 7. Developing Generative AI Applications with Governance and Security 8. Towards Artificial General Intelligence



Mastering Llm Applications With Langchain And Hugging Face


Mastering Llm Applications With Langchain And Hugging Face
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Author : Hunaidkhan Pathan
language : en
Publisher: BPB Publications
Release Date : 2024-09-21

Mastering Llm Applications With Langchain And Hugging Face written by Hunaidkhan Pathan and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-21 with Computers categories.


DESCRIPTION The book is all about the basics of NLP, generative AI, and their specific component LLM. In this book, we have provided conceptual knowledge about different terminologies and concepts of NLP and NLG with practical hands-on. This comprehensive book offers a deep dive into the world of NLP and LLMs. Starting with the fundamentals of Python programming and code editors, the book gradually introduces NLP concepts, including text preprocessing, word embeddings, and transformer architectures. You will explore the architecture and capabilities of popular models like GPT-3 and BERT. The book also covers practical aspects of LLM usage for RAG applications using frameworks like LangChain and Hugging Face and deploying them in real world applications. With a focus on both theoretical knowledge and hands-on experience, this book is ideal for anyone looking to master the art of NLP and LLMs. The book also contains AWS Cloud deployment, which will help readers step into the world of cloud computing. As the book contains both theoretical and practical approaches, it will help the readers to gain confidence in the deployment of LLMs for any use cases, as well as get acquainted with the required generative AI knowledge to crack the interviews. KEY FEATURES ● Covers Python basics, NLP concepts, and terminologies, including LLM and RAG concepts. ● Provides exposure to LangChain, Hugging Face ecosystem, and chatbot creation using custom data. ● Guides on integrating chatbots with real-time applications and deploying them on AWS Cloud. WHAT YOU WILL LEARN ● Basics of Python, which contains Python concepts, installation, and code editors. ● Foundation of NLP and generative AI concepts and different terminologies being used in NLP and generative AI domain. ● LLMs and their importance in the cutting edge of AI. ● Creating chatbots using custom data using open source LLMs without spending a single penny. ● Integration of chatbots with real-world applications like Telegram. WHO THIS BOOK IS FOR This book is ideal for beginners and freshers entering the AI or ML field, as well as those at an intermediate level looking to deepen their understanding of generative AI, LLMs, and cloud deployment. TABLE OF CONTENTS 1. Introduction to Python and Code Editors 2. Installation of Python, Required Packages, and Code Editors 3. Ways to Run Python Scripts 4. Introduction to NLP and its Concepts 5. Introduction to Large Language Models 6. Introduction of LangChain, Usage and Importance 7. Introduction of Hugging Face, its Usage and Importance 8. Creating Chatbots Using Custom Data with LangChain and Hugging Face Hub 9. Hyperparameter Tuning and Fine Tuning Pre-Trained Models 10. Integrating LLMs into Real-World Applications–Case Studies 11. Deploying LLMs in Cloud Environments for Scalability 12. Future Directions: Advances in LLMs and Beyond Appendix A: Useful Tips for Efficient LLM Experimentation Appendix B: Resources and References



The Llm Advantage How To Unlock The Power Of Language Models For Business Success


The Llm Advantage How To Unlock The Power Of Language Models For Business Success
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Author : Asish Dash
language : en
Publisher: Grazing Minds Publishing
Release Date : 2023-11-10

The Llm Advantage How To Unlock The Power Of Language Models For Business Success written by Asish Dash and has been published by Grazing Minds Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-10 with Business & Economics categories.


"The LLM Advantage: How to Harness the Power of Language, Logic, and Math Models for Your Business Success" is a comprehensive guide for individuals navigating the dynamic landscape of 21st-century business. Authored by Asish Dash, an experienced investor and entrepreneur with over a decade in technology startups, this book delves into the transformative realm of artificial intelligence, natural language processing, and data science. From ideation to execution to optimization, readers will explore the crucial role of Language, Logic, and Math Models (LLMs) in generating ideas, validating assumptions, building products, attracting customers, and improving overall business performance. Through real-world examples featuring prominent LLMs like GPT-3, BERT, and OpenAI Codex, the book illustrates how these models can interact with and understand natural language. It also examines the profound impact of LLMs on diverse business aspects, including product development, marketing, customer service, operations, strategy, and management. With insights from both successful and unsuccessful entrepreneurs, readers will gain valuable perspectives on navigating the opportunities and challenges posed by LLMs. The book provides a roadmap for developing the mindset, skills, and attributes of an LLM entrepreneur, offering practical tips, tools, and case studies for leveraging LLMs in business projects. Additionally, it addresses the ethical, legal, and technical considerations inherent in LLM entrepreneurship, guiding readers on best practices and risk mitigation. Closing with a forward-looking exploration of untapped potentials and emerging trends in LLM entrepreneurship, the book equips readers to discover new markets, industries, and innovations. The concluding chapter summarizes key takeaways, providing encouragement, inspiration, and resources for further exploration.



The Complete Llm Engineer S Handbook From Conceptualization To Production Of Large Language Models


The Complete Llm Engineer S Handbook From Conceptualization To Production Of Large Language Models
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Author : Sammy Oneal
language : en
Publisher: DIGITAL BLUE INC.
Release Date : 2025-04-07

The Complete Llm Engineer S Handbook From Conceptualization To Production Of Large Language Models written by Sammy Oneal and has been published by DIGITAL BLUE INC. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-07 with Computers categories.


The world of Large Language Models (LLMs) is rapidly evolving, transforming industries and redefining the boundaries of artificial intelligence. "The Complete LLM Engineer's Handbook: From Conceptualization to Production of Large Language Models" is your comprehensive guide to understanding and mastering this cutting-edge technology. This book offers a thorough exploration of LLMs, from their foundational concepts to their practical applications in real-world scenarios. Whether you are a seasoned engineer, a curious researcher, or a tech enthusiast, this handbook is designed to equip you with the knowledge and skills needed to navigate the complexities of LLMs. This book delves into the intricate process of developing and deploying LLMs, providing a step-by-step approach that covers everything from the initial conceptualization to the final production stages. Readers will gain insights into the theoretical underpinnings of LLMs, including the latest advancements in natural language processing and machine learning. Practical examples and case studies are interspersed throughout the text, illustrating how these models can be fine-tuned and optimized for various applications, such as chatbots, content generation, and data analysis.



Llm Architectures A Comprehensive Guide Bert Bart Xlnet


Llm Architectures A Comprehensive Guide Bert Bart Xlnet
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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :

Llm Architectures A Comprehensive Guide Bert Bart Xlnet written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.


Demystifying the Power of Large Language Models: A Guide for Everyone Large Language Models (LLMs) are revolutionizing the way we interact with machines and information. This comprehensive guide unveils the fascinating world of LLMs, guiding you from their fundamental concepts to their cutting-edge applications. Master the Basics: Explore the foundational architectures like Recurrent Neural Networks (RNNs) and Transformers that power LLMs. Gain a clear understanding of how these models process and understand language. Deep Dives into Pioneering Architectures: Delve into the specifics of BERT, BART, and XLNet, three groundbreaking LLM architectures. Learn about their unique pre-training techniques and how they tackle various natural language processing tasks. Unveiling the Champions: A Comparative Analysis: Discover how these leading LLM architectures stack up against each other. Explore performance benchmarks and uncover the strengths and weaknesses of each model to understand which one is best suited for your specific needs. Emerging Frontiers: Charting the Course for the Future: Explore the exciting trends shaping the future of LLMs. Learn about the quest for ever-larger models, the growing focus on training efficiency, and the development of specialized architectures for tasks like question answering and dialogue systems. This book is not just about technical details. It provides real-world case studies and use cases, showcasing how LLMs are transforming various industries, from content creation and customer service to healthcare and education. With clear explanations and a conversational tone, this guide is perfect for anyone who wants to understand the power of LLMs and their potential impact on our world. Whether you're a tech enthusiast, a student, or a professional curious about the future of AI, this book is your one-stop guide to demystifying Large Language Models.



The Llm Engineer S Playbook Mastering The Development Of Large Language Models For Real World Applications


The Llm Engineer S Playbook Mastering The Development Of Large Language Models For Real World Applications
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Author : Leona Lang
language : en
Publisher: DIGITAL BLUE INC.
Release Date : 2025-03-31

The Llm Engineer S Playbook Mastering The Development Of Large Language Models For Real World Applications written by Leona Lang and has been published by DIGITAL BLUE INC. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Computers categories.


The world of artificial intelligence is rapidly evolving, and at the heart of this revolution are Large Language Models (LLMs). These powerful tools are transforming how we interact with technology, offering unprecedented capabilities in natural language processing. The LLM Engineer's Playbook is an essential guide for anyone looking to navigate the complexities of developing and deploying LLMs in practical, real-world scenarios. This book provides a comprehensive roadmap for engineers, developers, and tech enthusiasts eager to harness the potential of LLMs, offering a blend of theoretical insights and hands-on techniques. Within these pages, you'll find a rich array of content designed to elevate your understanding and skills in LLM development. The book covers foundational concepts, ensuring even those new to the field can follow along, and progressively delves into more advanced topics. Key sections include the architecture and functioning of LLMs, data preparation and preprocessing, model training and fine-tuning, and best practices for deployment and maintenance. Each chapter is crafted to build on the previous one, creating a seamless learning experience. The practical examples and case studies illustrate how LLMs can be applied in various industries, from enhancing customer service chatbots to revolutionizing content creation and beyond.



Llm Design Patterns


Llm Design Patterns
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Author : Ken Huang
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-30

Llm Design Patterns written by Ken Huang and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Computers categories.


Explore reusable design patterns, including data-centric approaches, model development, model fine-tuning, and RAG for LLM application development and advanced prompting techniques Key Features Learn comprehensive LLM development, including data prep, training pipelines, and optimization Explore advanced prompting techniques, such as chain-of-thought, tree-of-thought, RAG, and AI agents Implement evaluation metrics, interpretability, and bias detection for fair, reliable models Print or Kindle purchase includes a free PDF eBook Book DescriptionThis practical guide for AI professionals enables you to build on the power of design patterns to develop robust, scalable, and efficient large language models (LLMs). Written by a global AI expert and popular author driving standards and innovation in Generative AI, security, and strategy, this book covers the end-to-end lifecycle of LLM development and introduces reusable architectural and engineering solutions to common challenges in data handling, model training, evaluation, and deployment. You’ll learn to clean, augment, and annotate large-scale datasets, architect modular training pipelines, and optimize models using hyperparameter tuning, pruning, and quantization. The chapters help you explore regularization, checkpointing, fine-tuning, and advanced prompting methods, such as reason-and-act, as well as implement reflection, multi-step reasoning, and tool use for intelligent task completion. The book also highlights Retrieval-Augmented Generation (RAG), graph-based retrieval, interpretability, fairness, and RLHF, culminating in the creation of agentic LLM systems. By the end of this book, you’ll be equipped with the knowledge and tools to build next-generation LLMs that are adaptable, efficient, safe, and aligned with human values. What you will learn Implement efficient data prep techniques, including cleaning and augmentation Design scalable training pipelines with tuning, regularization, and checkpointing Optimize LLMs via pruning, quantization, and fine-tuning Evaluate models with metrics, cross-validation, and interpretability Understand fairness and detect bias in outputs Develop RLHF strategies to build secure, agentic AI systems Who this book is for This book is essential for AI engineers, architects, data scientists, and software engineers responsible for developing and deploying AI systems powered by large language models. A basic understanding of machine learning concepts and experience in Python programming is a must.