Hands On Large Language Models
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Hands On Large Language Models
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Author : Jay Alammar
language : en
Publisher:
Release Date : 2024-12-03
Hands On Large Language Models written by Jay Alammar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-03 with Computers categories.
AI has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise of new features, products, and entire industries. With this book, Python developers will learn the practical tools and concepts they need to use these capabilities today. You'll learn how to use the power of pretrained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; build systems that classify and cluster text to enable scalable understanding of large numbers of text documents; and use existing libraries and pretrained models for text classification, search, and clusterings. This book also shows you how to: Build advanced LLM pipelines to cluster text documents and explore the topics they belong to Build semantic search engines that go beyond keyword search with methods like dense retrieval and rerankers Learn various use cases where these models can provide value Understand the architecture of underlying Transformer models like BERT and GPT Get a deeper understanding of how LLMs are trained Optimize LLMs for specific applications with methods such as generative model fine-tuning, contrastive fine-tuning, and in-context learning
Hands On Large Language Models
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Author : Jay Alammar
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-09-11
Hands On Large Language Models written by Jay Alammar 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 2024-09-11 with Computers categories.
AI has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise of new features, products, and entire industries. With this book, Python developers will learn the practical tools and concepts they need to use these capabilities today. You'll learn how to use the power of pre-trained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; build systems that classify and cluster text to enable scalable understanding of large amounts of text documents; and use existing libraries and pre-trained models for text classification, search, and clusterings. This book also shows you how to: Build advanced LLM pipelines to cluster text documents and explore the topics they belong to Build semantic search engines that go beyond keyword search with methods like dense retrieval and rerankers Learn various use cases where these models can provide value Understand the architecture of underlying Transformer models like BERT and GPT Get a deeper understanding of how LLMs are trained Understanding how different methods of fine-tuning optimize LLMs for specific applications (generative model fine-tuning, contrastive fine-tuning, in-context learning, etc.)
Hands On Large Language Models
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Author : Jay Alammar
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-09-11
Hands On Large Language Models written by Jay Alammar 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 2024-09-11 with Computers categories.
AI has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise of new features, products, and entire industries. With this book, Python developers will learn the practical tools and concepts they need to use these capabilities today. You'll learn how to use the power of pre-trained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; build systems that classify and cluster text to enable scalable understanding of large amounts of text documents; and use existing libraries and pre-trained models for text classification, search, and clusterings. This book also shows you how to: Build advanced LLM pipelines to cluster text documents and explore the topics they belong to Build semantic search engines that go beyond keyword search with methods like dense retrieval and rerankers Learn various use cases where these models can provide value Understand the architecture of underlying Transformer models like BERT and GPT Get a deeper understanding of how LLMs are trained Understanding how different methods of fine-tuning optimize LLMs for specific applications (generative model fine-tuning, contrastive fine-tuning, in-context learning, etc.)
Mastering Large Language Models With Python
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Author : Raj Arun R
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-04-12
Mastering Large Language Models With Python written by Raj Arun R and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-12 with Computers categories.
A Comprehensive Guide to Leverage Generative AI in the Modern Enterprise KEY FEATURES ● Gain a comprehensive understanding of LLMs within the framework of Generative AI, from foundational concepts to advanced applications. ● Dive into practical exercises and real-world applications, accompanied by detailed code walkthroughs in Python. ● Explore LLMOps with a dedicated focus on ensuring trustworthy AI and best practices for deploying, managing, and maintaining LLMs in enterprise settings. ● Prioritize the ethical and responsible use of LLMs, with an emphasis on building models that adhere to principles of fairness, transparency, and accountability, fostering trust in AI technologies. DESCRIPTION “Mastering Large Language Models with Python” is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both open-source and proprietary LLMs, the book delves into foundational concepts and advanced techniques, empowering professionals to harness the full potential of these models. Detailed discussions on quantization techniques for efficient deployment, operational strategies with LLMOps, and ethical considerations ensure a well-rounded understanding of LLM implementation. Through real-world case studies, code snippets, and practical examples, readers will navigate the complexities of LLMs with confidence, paving the way for innovative solutions and organizational growth. Whether you seek to deepen your understanding, drive impactful applications, or lead AI-driven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence. WHAT WILL YOU LEARN ● In-depth study of LLM architecture and its versatile applications across industries. ● Harness open-source and proprietary LLMs to craft innovative solutions. ● Implement LLM APIs for a wide range of tasks spanning natural language processing, audio analysis, and visual recognition. ● Optimize LLM deployment through techniques such as quantization and operational strategies like LLMOps, ensuring efficient and scalable model usage. ● Master prompt engineering techniques to fine-tune LLM outputs, enhancing quality and relevance for diverse use cases. ● Navigate the complex landscape of ethical AI development, prioritizing responsible practices to drive impactful technology adoption and advancement. WHO IS THIS BOOK FOR? This book is tailored for software engineers, data scientists, AI researchers, and technology leaders with a foundational understanding of machine learning concepts and programming. It's ideal for those looking to deepen their knowledge of Large Language Models and their practical applications in the field of AI. If you aim to explore LLMs extensively for implementing inventive solutions or spearheading AI-driven projects, this book is tailored to your needs. TABLE OF CONTENTS 1. The Basics of Large Language Models and Their Applications 2. Demystifying Open-Source Large Language Models 3. Closed-Source Large Language Models 4. LLM APIs for Various Large Language Model Tasks 5. Integrating Cohere API in Google Sheets 6. Dynamic Movie Recommendation Engine Using LLMs 7. Document-and Web-based QA Bots with Large Language Models 8. LLM Quantization Techniques and Implementation 9. Fine-tuning and Evaluation of LLMs 10. Recipes for Fine-Tuning and Evaluating LLMs 11. LLMOps - Operationalizing LLMs at Scale 12. Implementing LLMOps in Practice Using MLflow on Databricks 13. Mastering the Art of Prompt Engineering 14. Prompt Engineering Essentials and Design Patterns 15. Ethical Considerations and Regulatory Frameworks for LLMs 16. Towards Trustworthy Generative AI (A Novel Framework Inspired by Symbolic Reasoning) Index
Designing Large Language Model Applications
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Author : Suhas Pai
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-03-06
Designing Large Language Model Applications written by Suhas Pai 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 2025-03-06 with Computers categories.
Large language models (LLMs) have proven themselves to be powerful tools for solving a wide range of tasks, and enterprises have taken note. But transitioning from demos and prototypes to full-fledged applications can be difficult. This book helps close that gap, providing the tools, techniques, and playbooks that practitioners need to build useful products that incorporate the power of language models. Experienced ML researcher Suhas Pai offers practical advice on harnessing LLMs for your use cases and dealing with commonly observed failure modes. You’ll take a comprehensive deep dive into the ingredients that make up a language model, explore various techniques for customizing them such as fine-tuning, learn about application paradigms like RAG (retrieval-augmented generation) and agents, and more. Understand how to prepare datasets for training and fine-tuning Develop an intuition about the Transformer architecture and its variants Adapt pretrained language models to your own domain and use cases Learn effective techniques for fine-tuning, domain adaptation, and inference optimization Interface language models with external tools and data and integrate them into an existing software ecosystem
A Beginner S Guide To Large Language Models
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Author : Enamul Haque
language : en
Publisher: Enamul Haque
Release Date : 2024-07-25
A Beginner S Guide To Large Language Models written by Enamul Haque and has been published by Enamul Haque this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-25 with Computers categories.
A Beginner's Guide to Large Language Models: Conversational AI for Non-Technical Enthusiasts Step into the revolutionary world of artificial intelligence with "A Beginner's Guide to Large Language Models: Conversational AI for Non-Technical Enthusiasts." Whether you're a curious individual or a professional seeking to leverage AI in your field, this book demystifies the complexities of large language models (LLMs) with engaging, easy-to-understand explanations and practical insights. Explore the fascinating journey of AI from its early roots to the cutting-edge advancements that power today's conversational AI systems. Discover how LLMs, like ChatGPT and Google's Gemini, are transforming industries, enhancing productivity, and sparking creativity across the globe. With the guidance of this comprehensive and accessible guide, you'll gain a solid understanding of how LLMs work, their real-world applications, and the ethical considerations they entail. Packed with vivid examples, hands-on exercises, and real-life scenarios, this book will empower you to harness the full potential of LLMs. Learn to generate creative content, translate languages in real-time, summarise complex information, and even develop AI-powered applications—all without needing a technical background. You'll also find valuable insights into the evolving job landscape, equipping you with the knowledge to pursue a successful career in this dynamic field. This guide ensures that AI is not just an abstract concept but a tangible tool you can use to transform your everyday life and work. Dive into the future with confidence and curiosity, and discover the incredible possibilities that large language models offer. Join the AI revolution and unlock the secrets of the technology that's reshaping our world. "A Beginner's Guide to Large Language Models" is your key to understanding and mastering the power of conversational AI. Introduction This introduction sets the stage for understanding the evolution of artificial intelligence (AI) and large language models (LLMs). It highlights the promise of making complex AI concepts accessible to non-technical readers and outlines the unique approach of this book. Chapter 1: Demystifying AI and LLMs: A Journey Through Time This chapter introduces the basics of AI, using simple analogies and real-world examples. It traces the evolution of AI, from rule-based systems to machine learning and deep learning, leading to the emergence of LLMs. Key concepts such as tokens, vocabulary, and embeddings are explained to build a solid foundation for understanding how LLMs process and generate language. Chapter 2: Mastering Large Language Models Delving deeper into the mechanics of LLMs, this chapter covers the transformer architecture, attention mechanisms, and the processes involved in training and fine-tuning LLMs. It includes hands-on exercises with prompts and discusses advanced techniques like chain-of-thought prompting and prompt chaining to optimise LLM performance. Chapter 3: The LLM Toolbox: Unleashing the Power of Language AI This chapter explores the diverse applications of LLMs in text generation, language translation, summarisation, question answering, and code generation. It also introduces multimodal LLMs that handle both text and images, showcasing their impact on various creative and professional fields. Practical examples and real-life scenarios illustrate how these tools can enhance productivity and creativity. Chapter 4: LLMs in the Real World: Transforming Industries Highlighting the transformative impact of LLMs across different industries, this chapter covers their role in healthcare, finance, education, creative industries, and business. It discusses how LLMs are revolutionising tasks such as medical diagnosis, fraud detection, personalised tutoring, and content creation, and explores the future of work in an AI-powered world. Chapter 5: The Dark Side of LLMs: Ethical Concerns and Challenges Addressing the ethical challenges of LLMs, this chapter covers bias and fairness, privacy concerns, misuse of LLMs, security threats, and the transparency of AI decision-making. It also discusses ethical frameworks for responsible AI development and presents diverse perspectives on the risks and benefits of LLMs. Chapter 6: Mastering LLMs: Advanced Techniques and Strategies This chapter focuses on advanced techniques for leveraging LLMs, such as combining transformers with other AI models, fine-tuning open-source LLMs for specific tasks, and building LLM-powered applications. It provides detailed guidance on prompt engineering for various applications and includes a step-by-step guide to creating an AI-powered chatbot. Chapter 7: LLMs and the Future: A Glimpse into Tomorrow Looking ahead, this chapter explores emerging trends and potential breakthroughs in AI and LLM research. It discusses ethical AI development, insights from leading AI experts, and visions of a future where LLMs are integrated into everyday life. The chapter highlights the importance of building responsible AI systems that address societal concerns. Chapter 8: Your LLM Career Roadmap: Navigating the AI Job Landscape Focusing on the growing demand for LLM expertise, this chapter outlines various career paths in the AI field, such as LLM scientists, engineers, and prompt engineers. It provides resources for building the necessary skillsets and discusses the evolving job market, emphasising the importance of continuous learning and adaptability in a rapidly changing industry. Thought-Provoking Questions, Simple Exercises, and Real-Life Scenarios The book concludes with practical exercises and real-life scenarios to help readers apply their knowledge of LLMs. It includes thought-provoking questions to deepen understanding and provides resources and tools for further exploration of LLM applications. Tools to Help with Your Exercises This section lists tools and platforms for engaging with LLM exercises, such as OpenAI's Playground, Google Translate, and various IDEs for coding. Links to these tools are provided to facilitate hands-on learning and experimentation.
Transforming Conversational Ai
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Author : Michael McTear
language : en
Publisher: Springer Nature
Release Date : 2024-02-24
Transforming Conversational Ai written by Michael McTear and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-24 with Business & Economics categories.
Acquire the knowledge needed to work effectively in conversational artificial intelligence (AI) and understand the opportunities and threats it can potentially bring. This book will help you navigate from the traditional world of dialogue systems that revolve around hard coded scripts, to the world of large language models, prompt engineering, conversational AI platforms, multi-modality, and ultimately autonomous agents. In this new world, decisions are made by a system that may forever remain a ‘black box’ for most of us. This book aims to eliminate unnecessary noise and describe the fundamental components of conversational AI. Past experiences will prove invaluable in constructing seamless hybrid systems. This book will provide the most recommended solutions, recognizing that it is not always necessary to blindly pursue new tools. Written in unprecedented and turbulent times for conversational interfaces you’ll see that despite previous waves of advancement in conversational technology, now conversational interfaces are gaining unparalleled popularity. Specifically, the release of ChatGPT in November 2022 by Open AI revolutionized the conversational paradigm and showed how easy and intuitive communication with a computer can be. Old professions are being disrupted, new professions are emerging, and even the most conservative corporations are changing their strategy and experimenting with large language models, allocating an unprecedented amount of budget to these projects. No one knows for sure the exact future of conversational AI, but everyone agrees that it’s here to stay. What You'll Learn See how large language models are constructed and used in conversational systems Review the risks and challenges of new technologies in conversational AI Examine techniques for prompt engineering Enable practitioners to keep abreast of recent developments in conversational AI Who This Book Is For Conversation designers, product owners, and product or project managers in conversational AI who wish to learn about new methods and challenges posed by the recent emergence in the public domain of ChatGPT. Data scientists, final year undergraduates and graduates of computer science
Mastering Large Language Models
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Author : Virversity Online Courses
language : en
Publisher: eBookIt.com
Release Date : 2025-03-25
Mastering Large Language Models written by Virversity Online Courses and has been published by eBookIt.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-25 with Computers categories.
Delve into the transformative world of large language models with our comprehensive course designed to equip you with the knowledge and skills necessary to harness their full potential. This course offers students a deep dive into the foundational concepts, architecture, and applications of large language models, ensuring a thorough understanding of this cutting-edge technology and its impact across various domains. Master Large Language Models for Real-World Applications Build a strong foundation in the principles and historical development of large language models. Gain insights into the architecture and core components that make these models so powerful. Master the processes of text tokenization and word embeddings for better model efficiency. Learn about ethical considerations and the future directions of language model development. Acquire practical skills through hands-on practice with language model evaluation and fine-tuning. Explore the Impact and Utility of Large Language Models Large language models are at the forefront of artificial intelligence, revolutionizing how machines interpret and generate human language. In the initial stages of the course, we introduce you to the foundational concepts, guiding you through the history and evolution of language models. Understanding the architectural structures that underpin these models is crucial, and this course breaks down the core components, providing clarity on how they function cohesively. The intermediate modules will immerse you in core concepts such as tokenization and word embeddings, which are pivotal for enhancing model performance. You will learn about popular language models and the different datasets and techniques utilized during their training. Ethical considerations hold significant importance, and we dedicate a comprehensive section on the ethical challenges faced in deploying language models, ensuring you are aware of the responsibilities tied to their use. Practical application is a key emphasis of this course. With hands-on practice, you will evaluate and fine-tune a simple language model, equipping you with skills you can immediately apply to real-world scenarios. By learning how to integrate these models into applications, you'll be prepared to leverage their full potential in your projects. By the end of this course, you will be well-equipped to tap into the transformative power of large language models, with a keen understanding of both their technical and ethical implications. You will emerge with the ability to navigate the complexities of these models and their applications, ready to contribute to innovation in your field.
Large Language Models
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Author : John Atkinson-Abutridy
language : en
Publisher: CRC Press
Release Date : 2024-10-17
Large Language Models written by John Atkinson-Abutridy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-17 with Computers categories.
This book serves as an introduction to the science and applications of Large Language Models (LLMs). You'll discover the common thread that drives some of the most revolutionary recent applications of artificial intelligence (AI): from conversational systems like ChatGPT or BARD, to machine translation, summary generation, question answering, and much more. At the heart of these innovative applications is a powerful and rapidly evolving discipline, natural language processing (NLP). For more than 60 years, research in this science has been focused on enabling machines to efficiently understand and generate human language. The secrets behind these technological advances lie in LLMs, whose power lies in their ability to capture complex patterns and learn contextual representations of language. How do these LLMs work? What are the available models and how are they evaluated? This book will help you answer these and many other questions. With a technical but accessible introduction: •You will explore the fascinating world of LLMs, from its foundations to its most powerful applications •You will learn how to build your own simple applications with some of the LLMs Designed to guide you step by step, with six chapters combining theory and practice, along with exercises in Python on the Colab platform, you will master the secrets of LLMs and their application in NLP. From deep neural networks and attention mechanisms, to the most relevant LLMs such as BERT, GPT-4, LLaMA, Palm-2 and Falcon, this book guides you through the most important achievements in NLP. Not only will you learn the benchmarks used to evaluate the capabilities of these models, but you will also gain the skill to create your own NLP applications. It will be of great value to professionals, researchers and students within AI, data science and beyond.
Proceedings Of The International Conference On Smart Cities Volume 2
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Author : Hisham Mohamad
language : en
Publisher: Springer Nature
Release Date : 2025-07-25
Proceedings Of The International Conference On Smart Cities Volume 2 written by Hisham Mohamad and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-25 with Computers categories.
This book contains papers presented at the International Conference on Smart Cities (ICSC 2024) under the banner of World Engineering, Science & Technology Congress (ESTCON 2024) held from September 10 to 11, at Sabah International Convention Centre, Kota Kinabalu, Malaysia. The conference contains papers presented by academics and industrial practitioners showcasing their latest advancements and findings in emerging smart cities and sustainable urban living. The papers are categorized under the following tracks and topics of research: (1) Sustainable Engineering for Building; (2) Blockchain and Cybersecurity; (3) Artificial Intelligence (AI); (4) Smart Transportation System; and (5) Low-Carbon Planning for Sustainable City.