Concept Drift In Large Language Models
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Concept Drift In Large Language Models
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Author : Ketan Sanjay Desale
language : en
Publisher: CRC Press
Release Date : 2025-05-08
Concept Drift In Large Language Models written by Ketan Sanjay Desale and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-08 with Computers categories.
This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. It discusses the theoretical basis of concept drift and its consequences for large language models, particularly the transformative power of cutting-edge models such as GPT-3.5 and GPT-4. It offers real-world case studies to observe firsthand how concept drift influences the performance of language models in a variety of circumstances, delivering valuable lessons learnt and actionable takeaways. The book is designed for professionals, AI practitioners, and scholars, focused on natural language processing, machine learning, and artificial intelligence. • Examines concept drift in AI, particularly its impact on large language models • Analyses how concept drift affects large language models and its theoretical and practical consequences • Covers detection methods and practical implementation challenges in language models • Showcases examples of concept drift in GPT models and lessons learnt from their performance • Identifies future research avenues and recommendations for practitioners tackling concept drift in large language models
Concept Drift In Large Language Models
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Author : Ketan Sanjay Desale
language : en
Publisher: C&h/CRC Press
Release Date : 2025-07
Concept Drift In Large Language Models written by Ketan Sanjay Desale and has been published by C&h/CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07 with Computers categories.
"This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. It discusses the theoretical basis of concept drift and its consequences for large language models, particularly the transformative power of cutting-edge models such as GPT-3.5 and GPT-4. It offers real-world case studies to observe firsthand how concept drift influences the performance of language models in a variety of circumstances, delivering valuable lessons learned and actionable takeaways. The book is designed for professionals, AI practitioners, and scholars, focused on natural language processing, machine learning, and artificial intelligence. Examines concept drift in AI, particularly its impact on large language models Analyses how concept drift affects large language models and its theoretical and practical consequences Covers detection methods and practical implementation challenges in language models Showcases examples of concept drift in GPT models and lessons learned from their performance Identifies future research avenues and recommendations for practitioners tackling concept drift in large language models"-- Provided by publisher.
Scaling Enterprise Solutions With Large Language Models
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Author : Arindam Ganguly
language : en
Publisher: Springer Nature
Release Date : 2025-05-20
Scaling Enterprise Solutions With Large Language Models written by Arindam Ganguly and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-20 with Computers categories.
Artificial Intelligence (AI) is the bedrock of today's applications, propelling the field towards Artificial General Intelligence (AGI). Despite this advancement, integrating such breakthroughs into large-scale production-grade enterprise applications presents significant challenges. This book addresses these hurdles in the domain of large language models within enterprise solutions. By leveraging Big Data engineering and popular data cataloguing tools, you’ll see how to transform challenges into opportunities, emphasizing data reuse for multiple AI models across diverse domains. You’ll gain insights into large language model behavior by using tools such as LangChain and LLamaIndex to segment vast datasets intelligently. Practical considerations take precedence, guiding you on effective AI Governance and data security, especially in data-sensitive industries like banking. This enterprise-focused book takes a pragmatic approach, ensuring large language models align with broader enterprise goals. From data gathering to deployment, it emphasizes the use of low code AI workflow tools for efficiency. Addressing the challenges of handling large volumes of data, the book provides insights into constructing robust Big Data pipelines tailored for Generative AI applications. Scaling Enterprise Solutions with Large Language Models will lead you through the Generative AI application lifecycle and provide the practical knowledge to deploy efficient Generative AI solutions for your business. What You Will Learn Examine the various phases of an AI Enterprise Applications implementation. Turn from AI engineer or Data Science to an Intelligent Enterprise Architect. Explore the seamless integration of AI in Big Data Pipelines. Manage pivotal elements surrounding model development, ensuring a comprehensive understanding of the complete application lifecycle. Plan and implement end-to-end large-scale enterprise AI applications with confidence. Who This Book Is For Enterprise Architects, Technical Architects, Project Managers and Senior Developers.
Discovering Drift Phenomena In Evolving Landscapes
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Author : Marco Piangerelli
language : en
Publisher: Springer Nature
Release Date : 2025-02-24
Discovering Drift Phenomena In Evolving Landscapes written by Marco Piangerelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-24 with Computers categories.
This book constitutes the post-conference proceedings of the First International Workshop on Discovering Drift Phenomena in Evolving Landscapes, DELTA 2024, held in Barcelona, Spain, on August 26, 2024. The 9 full papers presented together with 1 short paper were carefully reviewed and selected from 17 submissions. The papers are grouped into three topical sections, namely: adaptive and robust learning in dynamic environments; challenges and solutions in drift detection and anomaly explanation; and innovative approaches to concept drift detection and landscape shifts.
Principles Of Data Science
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Author : Sinan Ozdemir
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-01-31
Principles Of Data Science written by Sinan Ozdemir 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 2024-01-31 with Computers categories.
Transform your data into insights with must-know techniques and mathematical concepts to unravel the secrets hidden within your data Key Features Learn practical data science combined with data theory to gain maximum insights from data Discover methods for deploying actionable machine learning pipelines while mitigating biases in data and models Explore actionable case studies to put your new skills to use immediately Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPrinciples of Data Science bridges mathematics, programming, and business analysis, empowering you to confidently pose and address complex data questions and construct effective machine learning pipelines. This book will equip you with the tools to transform abstract concepts and raw statistics into actionable insights. Starting with cleaning and preparation, you’ll explore effective data mining strategies and techniques before moving on to building a holistic picture of how every piece of the data science puzzle fits together. Throughout the book, you’ll discover statistical models with which you can control and navigate even the densest or the sparsest of datasets and learn how to create powerful visualizations that communicate the stories hidden in your data. With a focus on application, this edition covers advanced transfer learning and pre-trained models for NLP and vision tasks. You’ll get to grips with advanced techniques for mitigating algorithmic bias in data as well as models and addressing model and data drift. Finally, you’ll explore medium-level data governance, including data provenance, privacy, and deletion request handling. By the end of this data science book, you'll have learned the fundamentals of computational mathematics and statistics, all while navigating the intricacies of modern ML and large pre-trained models like GPT and BERT.What you will learn Master the fundamentals steps of data science through practical examples Bridge the gap between math and programming using advanced statistics and ML Harness probability, calculus, and models for effective data control Explore transformative modern ML with large language models Evaluate ML success with impactful metrics and MLOps Create compelling visuals that convey actionable insights Quantify and mitigate biases in data and ML models Who this book is for If you are an aspiring novice data scientist eager to expand your knowledge, this book is for you. Whether you have basic math skills and want to apply them in the field of data science, or you excel in programming but lack the necessary mathematical foundations, you’ll find this book useful. Familiarity with Python programming will further enhance your learning experience.
Language Understanding With Luis
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-09
Language Understanding With Luis written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-09 with Computers categories.
"Language Understanding with LUIS" "Language Understanding with LUIS" is an in-depth, authoritative guide to mastering Microsoft’s Language Understanding Intelligent Service (LUIS), a pivotal technology at the heart of enterprise conversational AI. The book begins with a comprehensive exploration of natural language processing (NLP), tracing its historical roots and detailing the evolution of LUIS within today’s cloud-powered ecosystem. Readers are introduced to LUIS’s architecture, intent recognition, sophisticated entity extraction, and essential security considerations—laying the groundwork for building robust, scalable, and secure language applications. Progressing beyond foundational principles, the text offers a detailed roadmap for application design and data engineering tailored specifically to LUIS. Readers will find expert guidance on crafting diverse utterance corpora, structuring intents and entities for maximum coverage and specificity, and leveraging advanced techniques for data labeling and conflict management. The model training pipeline receives focused attention, including best practices for exploratory data analysis, supervised and transfer learning, distributed training, and precision optimization through hyperparameter tuning. Throughout, evaluation, monitoring, and continuous improvement are addressed with cutting-edge metrics, error analysis, and automation workflows. Bridging theory and real-world deployment, the book examines advanced modeling topics such as contextual intent resolution, dynamic entity handling, multilingual support, and scalable integration patterns with Azure and beyond. Enterprise-grade security, compliance, and operational excellence are explored in depth, providing clear strategies for authentication, privacy, governance, and cost optimization. The final chapters peer into the future of language AI, illuminating emerging trends such as integration with large language models, knowledge graphs, explainability, self-healing systems, and ethical considerations, making this book an indispensable resource for professionals and innovators building the next generation of intelligent conversational systems.
Building And Fine Tuning Llms From Scratch
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Author : StoryBuddiesPlay
language : en
Publisher: StoryBuddiesPlay
Release Date : 2024-09-10
Building And Fine Tuning Llms From Scratch written by StoryBuddiesPlay and has been published by StoryBuddiesPlay this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-10 with Computers categories.
"Building and Fine-Tuning LLMs from Scratch" is an essential guide for AI practitioners, researchers, and enthusiasts looking to master the art of creating and optimizing large language models. This comprehensive resource covers everything from fundamental concepts to cutting-edge techniques, providing readers with the knowledge and skills needed to develop state-of-the-art language AI systems. With practical examples, in-depth explanations, and expert insights, this book is your roadmap to becoming proficient in LLM architecture, training, fine-tuning, and deployment. Whether you're a seasoned professional or an ambitious newcomer, this guide will empower you to push the boundaries of what's possible in natural language processing and AI. Large Language Models, AI development, Natural Language Processing, Machine Learning, Deep Learning, Transformer Architecture, Fine-tuning techniques, Neural Networks, Text Generation, Language AI
Langchain Applications In Modern Llm Development
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Author : William Smith
language : en
Publisher: HiTeX Press
Release Date : 2025-07-24
Langchain Applications In Modern Llm Development written by William Smith and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-24 with Computers categories.
"LangChain Applications in Modern LLM Development" "LangChain Applications in Modern LLM Development" serves as the definitive guide to deploying, scaling, and optimizing Large Language Model (LLM) applications with the powerful LangChain framework. Beginning with an insightful exploration of the historical evolution of LLMs and the motivating philosophy behind LangChain, the book positions this framework at the forefront of contemporary AI tooling. Detailed comparisons showcase LangChain's unique modularity, broad ecosystem integrations, and extensibility, setting the stage for both newcomers and advanced practitioners to appreciate its architectural strengths. Through clear explanations of foundational concepts such as chains, prompt management, and memory handling, the book equips readers to design and orchestrate robust, context-aware LLM workflows. Advanced chapters delve deep into data integration, retrieval augmented generation, agent-driven reasoning, tool management, and multi-agent orchestration. Security, compliance, and observability are treated as first-class concerns, with comprehensive guidance on safeguarding workflows, detecting threats, and ensuring transparency across deployments. Readers are also introduced to proven strategies for quality assurance and continuous evaluation, ensuring lasting reliability in production environments. Closing with real-world case studies across diverse domains—including enterprise knowledge systems, document automation, research assistants, and regulated industries—the book illuminates the transformative power of LangChain in modern AI applications. Forward-looking chapters examine emerging trends, multi-framework interoperability, sustainability, and the evolving LangChain community, making this text an indispensable resource for anyone seeking to harness the full potential of LLM technologies in both current and future contexts.
Applied Computer Sciences In Engineering
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Author : Juan Carlos Figueroa-García
language : en
Publisher: Springer Nature
Release Date : 2024-10-17
Applied Computer Sciences In Engineering written by Juan Carlos Figueroa-García and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-17 with Computers categories.
The two-volume set CCIS 2222 + 2223 constitutes the proceedings of the 11th Workshop on Engineering Applications, WEA 2024, which took place in Barranquilla, Colombia, during October 23–25, 2024. The 42 full papers presented here were carefully reviewed and selected from 97 submissions. The papers are organized in the following topical sections: Part I - Artificial Intelligence. Part II - Optimization; Simulation; Applications.
Neural Symbolic Learning And Reasoning
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Author : Tarek R. Besold
language : en
Publisher: Springer Nature
Release Date : 2024-09-09
Neural Symbolic Learning And Reasoning written by Tarek R. Besold and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-09 with Computers categories.
This book constitutes the refereed proceedings of the 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024, held in Barcelona, Spain during September 9-12th, 2024. The 30 full papers and 18 short papers were carefully reviewed and selected from 89 submissions, which presented the latest and ongoing research work on neurosymbolic AI. Neurosymbolic AI aims to build rich computational models and systems by combining neural and symbolic learning and reasoning paradigms. This combination hopes to form synergies among their strengths while overcoming their complementary weaknesses.