Hands On Large Language Models
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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:
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
The Practical Guide To Large Language Models
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Author : Ivan Gridin
language : en
Publisher: Apress
Release Date : 2025-12-13
The Practical Guide To Large Language Models written by Ivan Gridin and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-13 with Computers categories.
This book is a practical guide to harnessing Hugging Face's powerful transformers library, unlocking access to the largest open-source LLMs. By simplifying complex NLP concepts and emphasizing practical application, it empowers data scientists, machine learning engineers, and NLP practitioners to build robust solutions without delving into theoretical complexities. The book is structured into three parts to facilitate a step-by-step learning journey. Part One covers building production-ready LLM solutions introduces the Hugging Face library and equips readers to solve most of the common NLP challenges without requiring deep knowledge of transformer internals. Part Two focuses on empowering LLMs with RAG and intelligent agents exploring Retrieval-Augmented Generation (RAG) models, demonstrating how to enhance answer quality and develop intelligent agents. Part Three covers LLM advances focusing on expert topics such as model training, principles of transformer architecture and other cutting-edge techniques related to the practical application of language models. Each chapter includes practical examples, code snippets, and hands-on projects to ensure applicability to real-world scenarios. This book bridges the gap between theory and practice, providing professionals with the tools and insights to develop practical and efficient LLM solutions. What you will learn: What are the different types of tasks modern LLMs can solve How to select the most suitable pre-trained LLM for specific tasks How to enrich LLM with a custom knowledge base and build intelligent systems What are the core principles of Language Models, and how to tune them How to build robust LLM-based AI Applications Who this book is for: Data scientists, machine learning engineers, and NLP specialists with basic Python skills, introductory PyTorch knowledge, and a primary understanding of deep learning concepts, ready to start applying Large Language Models in practice.
Hands On Large Language Models
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Author : Jay Alammar
language : en
Publisher:
Release Date : 2025
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 2025 with Artificial intelligence categories.
How To Ai
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Author : Christopher Mims
language : en
Publisher: Crown Currency
Release Date : 2026-01-27
How To Ai written by Christopher Mims and has been published by Crown Currency this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-27 with Business & Economics categories.
A frank, hands-on guide to using AI at work, unpacking for the curious and skeptical alike the “24 Laws” of AI and revealing strategies that businesses of every size can use to free up time, innovate, and add to the bottom line—from a Wall Street Journal tech columnist “The antidote to AI panic. Read it. You’ll breathe easier.”—Scott Galloway, NYU Stern School of Business professor and co-host of Pivot with Kara Swisher “A clear, practical, and hype-free guide to the AI revolution that will resonate with anyone trying to figure out the how to make AI deliver real value.”—Ethan Mollick, Wharton professor and New York Times bestselling author of Co-Intelligence AI is nothing to be afraid of. After all, AI is merely software. It’s great at some things and (at least right now) terrible at others. But for workers who take time to experiment with AI and develop expertise, AI will make them more productive and more creative, saving them time, giving them job security, and boosting their income. In How to AI, Wall Street Journal columnist Christopher Mims introduces readers to people just like them who are at the forefront of using AI in the world of work. Imagine a freelance lawyer who suddenly has a whip-smart assistant to help her nail every deposition. Or a mom-and-pop contractor whose new software tool is automating construction bids that used to eat up hundreds of hours. But even as half a billion people around the world have leapt at the chance to use ChatGPT and other tools, millions of us have stayed on the sidelines. Are you one of them? Maybe you feel you should be using AI tools, but you don’t know where to begin. Or maybe you love AI but find yourself struggling to get your co-workers or employees on board. In How to AI, Mims teaches readers twenty-four simple but eye-opening “laws” about AI and how we should approach it, including: • AI is an assistant, not a replacement. • AI isn’t creative, but it can help you be. • Give AI your least favorites things to do. • AI can’t create finished products, but it’s great at prototypes. Animated by the wit and brilliant explanatory power that have earned Mims’s Wall Street Journal columns a devoted following, How to AI will prepare readers to become a part of the AI revolution—and, most important, arm them with the tools to make it work for them.
Langchain Llm
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Author : Morgan Devline
language : en
Publisher: Independently Published
Release Date : 2024-12-06
Langchain Llm written by Morgan Devline and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-06 with Computers categories.
LangChain helps you to revolutionize your approach to AI application development! Whether you're a developer, data scientist, or AI enthusiast, this book provides a comprehensive, hands-on guide to building intelligent, scalable, and efficient systems using LangChain and large language models (LLMs). Developing applications that leverage the power of LLMs can be complex and overwhelming. LangChain LLM simplifies the process, offering tools and workflows to seamlessly integrate LLMs into your projects. From creating dynamic chatbots to implementing advanced knowledge retrieval systems, this book equips you with the skills and knowledge to tackle real-world challenges with confidence. What You'll Learn Foundational Concepts: Understand the basics of LangChain and large language models, their applications, and their synergy in AI workflows. Building Applications: Create personalized chatbots, knowledge retrieval systems, and summarization tools. Advanced Features: Explore LangChain's memory, tool integrations, and multi-agent systems to design intelligent, context-aware applications. Deployment and Scaling: Learn how to deploy your AI applications on the cloud, optimize workflows for production, and handle high-traffic environments. Hands-On Practice: Dive into step-by-step projects and exercises, complete with clean, well-commented code examples and downloadable resources. Why Read This Book? Practical Focus: This isn't just theory. You'll actively build projects that mirror real-world use cases, from retrieval-augmented generation (RAG) systems to dynamic workflow generators. Cutting-Edge Techniques: Stay ahead of the curve with insights into the latest AI trends, including multi-modal LLMs and serverless architectures. Accessible for All Levels: Designed for both beginners and experienced developers, the book breaks down complex concepts into simple, actionable steps. Interactive Resources: Access a companion GitHub repository, coding challenges, and downloadable examples to enhance your learning experience. This book is perfect for: AI Developers looking to master LangChain and integrate LLMs into their workflows. Data Scientists seeking to build intelligent, data-driven applications. Tech Enthusiasts curious about the capabilities of modern AI technologies. Anyone eager to design, deploy, and scale AI solutions in a practical, hands-on way. What Readers Are Saying "This book demystifies LangChain and LLMs with clear examples and actionable insights." "A must-have guide for anyone looking to build real-world AI applications with LangChain." "Finally, a resource that makes advanced AI concepts approachable and practical!" If you're ready to harness the full potential of LangChain and transform your AI development skills, this book is your roadmap. Whether you're building your first chatbot or scaling a multi-agent system, LangChain LLM: A Hands-On Guide to Building and Deploying Large Language Model Applications will guide you every step of the way.
International Symposium On Computer Vision
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Author :
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 1995
International Symposium On Computer Vision written by and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
Eighth Ieee International Conference On Computer Vision
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Author : IEEE Computer Society
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 2001
Eighth Ieee International Conference On Computer Vision written by IEEE Computer Society and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
This two-volume set contains the proceedings of the July 2001 conference on computer vision. The 205 papers discuss sensors and early vision, stereo and multiple views, segmentation and matching, learning in vision, shape representation and recovery, stereo and multiple views, segmentation and matching, object recognition, tracking, video analysis, reflectance, image databases, vision systems and texture, and demo overviews. There is no subject index. The included CD-ROM contains a full version of the proceedings. c. Book News Inc.
Large Language Models A Deep Dive
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Author : Uday Kamath
language : en
Publisher: Springer Nature
Release Date : 2024-08-20
Large Language Models A Deep Dive written by Uday Kamath and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-20 with Computers categories.
Large Language Models (LLMs) have emerged as a cornerstone technology, transforming how we interact with information and redefining the boundaries of artificial intelligence. LLMs offer an unprecedented ability to understand, generate, and interact with human language in an intuitive and insightful manner, leading to transformative applications across domains like content creation, chatbots, search engines, and research tools. While fascinating, the complex workings of LLMs—their intricate architecture, underlying algorithms, and ethical considerations—require thorough exploration, creating a need for a comprehensive book on this subject. This book provides an authoritative exploration of the design, training, evolution, and application of LLMs. It begins with an overview of pre-trained language models and Transformer architectures, laying the groundwork for understanding prompt-based learning techniques. Next, it dives into methods for fine-tuning LLMs, integrating reinforcement learning for value alignment, and the convergence of LLMs with computer vision, robotics, and speech processing. The book strongly emphasizes practical applications, detailing real-world use cases such as conversational chatbots, retrieval-augmented generation (RAG), and code generation. These examples are carefully chosen to illustrate the diverse and impactful ways LLMs are being applied in various industries and scenarios. Readers will gain insights into operationalizing and deploying LLMs, from implementing modern tools and libraries to addressing challenges like bias and ethical implications. The book also introduces the cutting-edge realm of multimodal LLMs that can process audio, images, video, and robotic inputs. With hands-on tutorials for applying LLMs to natural language tasks, this thorough guide equips readers with both theoretical knowledge and practical skills for leveraging the full potential of large language models. This comprehensive resource is appropriate for a wide audience: students, researchers and academics in AI or NLP, practicing data scientists, and anyone looking to grasp the essence and intricacies of LLMs. Key Features: Over 100 techniques and state-of-the-art methods, including pre-training, prompt-based tuning, instruction tuning, parameter-efficient and compute-efficient fine-tuning, end-user prompt engineering, and building and optimizing Retrieval-Augmented Generation systems, along with strategies for aligning LLMs with human values using reinforcement learning Over 200 datasets compiled in one place, covering everything from pre- training to multimodal tuning, providing a robust foundation for diverse LLM applications Over 50 strategies to address key ethical issues such as hallucination, toxicity, bias, fairness, and privacy. Gain comprehensive methods for measuring, evaluating, and mitigating these challenges to ensure responsible LLM deployment Over 200 benchmarks covering LLM performance across various tasks, ethical considerations, multimodal applications, and more than 50 evaluation metrics for the LLM lifecycle Nine detailed tutorials that guide readers through pre-training, fine- tuning, alignment tuning, bias mitigation, multimodal training, and deploying large language models using tools and libraries compatible with Google Colab, ensuring practical application of theoretical concepts Over 100 practical tips for data scientists and practitioners, offering implementation details, tricks, and tools to successfully navigate the LLM life- cycle and accomplish tasks efficiently
Proceedings
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Author :
language : en
Publisher:
Release Date : 1999
Proceedings written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computer vision categories.