Intermediate Python And Large Language Models
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Intermediate Python And Large Language Models
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Author : Dilyan Grigorov
language : en
Publisher: Springer Nature
Release Date : 2025-06-27
Intermediate Python And Large Language Models written by Dilyan Grigorov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-27 with Computers categories.
Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications. The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, you’ll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency. The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. You’ll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations. By the end of the book, you’ll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction. What You Will Learn Understand the fundamentals of LangChain and Python for LLM development Know advanced AI workflows, including fine-tuning and memory management Build AI-powered applications such as chatbots, retrieval systems, and automation tools Know deployment strategies and performance optimization for real-world use Use best practices for scalability, security, and responsible AI implementation Unlock the full potential of LLMs and take your AI development skills to the next level Who This Book Is For Software engineers and Python developers interested in learning the foundations of LLMs and building advanced modern LLM applications for various tasks
The Practical Guide To Large Language Models
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Author : Ivan Gridin
language : en
Publisher: Springer Nature
Release Date : 2025-12-12
The Practical Guide To Large Language Models written by Ivan Gridin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-12 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.
Mastering Retrieval Augmented Generation
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Author : Ranajoy Bose
language : en
Publisher: Springer Nature
Release Date : 2026-01-01
Mastering Retrieval Augmented Generation written by Ranajoy Bose and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-01 with Computers categories.
Retrieval-Augmented Generation (RAG) represents the cutting edge of AI innovation, bridging the gap between large language models (LLMs) and real-world knowledge. This book provides the definitive roadmap for building, optimizing, and deploying enterprise-grade RAG systems that deliver measurable business value. This comprehensive guide takes you beyond basic concepts to advanced implementation strategies, covering everything from architectural patterns to production deployment. You'll explore proven techniques for document processing, vector optimization, retrieval enhancement, and system scaling, supported by real-world case studies from leading organizations. Key Learning Objectives Design and implement production-ready RAG architectures for diverse enterprise use cases Master advanced retrieval strategies including graph-based approaches and agentic systems Optimize performance through sophisticated chunking, embedding, and vector database techniques Navigate the integration of RAG with modern LLMs and generative AI frameworks Implement robust evaluation frameworks and quality assurance processes Deploy scalable solutions with proper security, privacy, and governance controls Real-World Applications Intelligent document analysis and knowledge extraction Code generation and technical documentation systems Customer support automation and decision support tools Regulatory compliance and risk management solutions Whether you're an AI engineer scaling existing systems or a technical leader planning next-generation capabilities, this book provides the expertise needed to succeed in the rapidly evolving landscape of enterprise AI. What You Will Learn Architecture Mastery: Design scalable RAG systems from prototype to enterprise production Advanced Retrieval: Implement sophisticated strategies, including graph-based and multi-modal approaches Performance Optimization: Fine-tune embedding models, vector databases, and retrieval algorithms for maximum efficiency LLM Integration: Seamlessly combine RAG with state-of-the-art language models and generative AI frameworks Production Excellence: Deploy robust systems with monitoring, evaluation, and continuous improvement processes Industry Applications: Apply RAG solutions across diverse enterprise sectors and use cases Who This Book Is For Primary audience: Senior AI/ML engineers, data scientists, and technical architects building production AI systems; secondary audience: Engineering managers, technical leads, and AI researchers working with large-scale language models and information retrieval systems Prerequisites: Intermediate Python programming, basic understanding of machine learning concepts, and familiarity with natural language processing fundamentals
Hugging Face In Action
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Author : Wei-Meng Lee
language : en
Publisher: Simon and Schuster
Release Date : 2025-11-11
Hugging Face In Action written by Wei-Meng Lee and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-11 with Computers categories.
Everything you need to know about using the tools, libraries, and models at Hugging Face—from transformers, to RAG, LangChain, and Gradio. Hugging Face in Action reveals how to get the absolute best out of everything Hugging Face, from accessing state-of-the-art models to building intuitive frontends for AI apps. With Hugging Face in Action you’ll learn: • Utilizing Hugging Face Transformers and Pipelines for NLP tasks • Applying Hugging Face techniques for Computer Vision projects • Manipulating Hugging Face Datasets for efficient data handling • Training Machine Learning models with AutoTrain functionality • Implementing AI agents for autonomous task execution • Developing LLM-based applications using LangChain and LlamaIndex • Constructing LangChain applications visually with LangFlow • Creating web-based user interfaces using Gradio • Building locally running LLM-based applications with GPT4ALL • Querying local data using Large Language Models Want a cutting edge transformer library? Hugging Face’s open source offering is best in class. Need somewhere to host your models? Hugging Face Spaces has you covered. Do your users need an intuitive frontend for your AI app? Hugging Face’s Gradio library makes it easy to build UI using the Python skills you already have. In Hugging Face in Action you’ll learn how to take full advantage of all of Hugging Face’s amazing features to quickly and reliably prototype and productionize AI applications. About the technology Hugging Face is an incredible open-source ecosystem for AI engineers and data scientists, providing hundreds of pre-trained models, datasets, tools, and libraries. It’s also a central hub for collaborating on leading edge AI research. Hugging Face is a massive platform, and this book will help you take full advantage of all it has to offer. About the book Hugging Face in Action teaches you how to build end-to-end AI systems using resources from the Hugging Face community. In it, you’ll create multiple projects, including an object detection model, a RAG Q&A application, an LLM-powered chatbot, and more. You’ll appreciate the clear, accessible explanations, along with thoughtful introductions to key technologies like LangChain, LlamaIndex, and Gradio. What's inside • How to navigate the huge Hugging Face library of models and tools • How to run LLMs locally using GPT4ALL • How to create web-based user interfaces using Gradio • How to improve models using Hugging Face datasets About the reader For Python programmers familiar with NumPy and Pandas. No AI experience required. About the author Wei-Meng Lee is a technologist and founder of Developer Learning Solutions. Table of Contents 1 Introducing Hugging Face 2 Getting started 3 Using Hugging Face transformers and pipelines for NLP tasks 4 Using Hugging Face for computer vision tasks 5 Exploring, tokenizing, and visualizing Hugging Face datasets 6 Fine-tuning pretrained models and working with multimodal models 7 Creating LLM-based applications using LangChain and LlamaIndex 8 Building LangChain applications visually using Langflow 9 Programming agents 10 Building a web-based UI using Gradio 11 Building locally running LLM-based applications using GPT4All 12 Using LLMs to query your local data 13 Bridging LLMs to the real world with the Model Context Protocol
Computing Internet Of Things And Data Analytics
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Author : Fausto Pedro García Márquez
language : en
Publisher: Springer Nature
Release Date : 2025-08-15
Computing Internet Of Things And Data Analytics written by Fausto Pedro García Márquez and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-15 with Computers categories.
This proceedings book offers a multidimensional exploration of the latest advancements in data science and technology, providing valuable insights for researchers, professionals, and enthusiasts in the rapidly evolving field. Each chapter delves into specific topics, offering a blend of theoretical foundations, practical applications, and future perspectives to keep readers abreast of the cutting-edge developments in these critical domains.
Advanced Applications Of Generative Ai And Natural Language Processing Models
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Author : Obaid, Ahmed J.
language : en
Publisher: IGI Global
Release Date : 2023-12-21
Advanced Applications Of Generative Ai And Natural Language Processing Models written by Obaid, Ahmed J. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-21 with Computers categories.
The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.
Intelligent Informatics
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Author : Sankar K. Pal
language : en
Publisher: Springer Nature
Release Date : 2024-10-17
Intelligent Informatics written by Sankar K. Pal 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 Technology & Engineering categories.
This book constitutes thoroughly refereed post-conference proceedings of the 8th International Symposium on Intelligent Informatics (ISI 2023), December 18–20, 2023, Bangalore, India. The revised papers presented were carefully reviewed and selected from several initial submissions. The scope of the symposium includes AI, machine learning, cognitive computing, soft computing, security informatics, data science, computer vision, pattern recognition, intelligent software engineering, intelligent networked systems, IoT, cyber-physical systems, and NLP. The book is directed to the researchers and scientists engaged in various fields of computing and network communication domains.
Advances In Computational Collective Intelligence
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Author : Ngoc Thanh Nguyen
language : en
Publisher: Springer Nature
Release Date : 2025-11-07
Advances In Computational Collective Intelligence written by Ngoc Thanh Nguyen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-07 with Computers categories.
This two-volume set CCIS 2747-2748 constitutes the refereed proceedings of the 17th International Conference on Computational Collective Intelligence, ICCCI 2025, held in Ho Chi Minh City, Vietnam, during November 12–15, 2025. The 67 full papers included in this book were carefully reviewed and selected from 290 submissions. The papers are organized in the following topical sections: Part I: Collective Intelligence and Collective Decision-Making; Cooperative Strategies for Decision Making and Optimization; Computational Intelligence for Digital Content Understanding; Data Fusion and Application for Industry 4.0; and Natural Language Processing. Part II: Deep Learning Techniques; Social Networks and Intelligent Systems; Computational Intelligence in Medical Applications; Data Mining and Machine Learning; and Cybersecurity, Blockchain Technology and Internet of Things.
Enterprise Information Systems
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Author : Slimane Hammoudi
language : en
Publisher: Springer Nature
Release Date : 2025-10-29
Enterprise Information Systems written by Slimane Hammoudi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-29 with Computers categories.
The two volume set LNBIP 566 - 567 constitutes the refereed post-conference proceedings of the 26th International Conference on Enterprise Information Systems, ICEIS 2024, which was held in Angers, France, during April 2024. The 19 full papers and 18 short papers presented were carefully reviewed and selected from 244 submissions. The proceedings also include one invited paper in full paper length. The purpose of the International Conference on Enterprise Information Systems (ICEIS) is to bring together researchers, engineers and practitioners interested in the advances and business applications of information systems, covering different aspects such as Enterprise Database Technology, Systems Integration, Artificial Intelligence, Decision Support Systems, Information Systems Analysis and Specification, Internet Computing, Electronic Commerce, Human-Computer Interaction and Enterprise Architecture.
Python For Generative Ai Llms
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Author : Thomas D Ullrich
language : en
Publisher: Independently Published
Release Date : 2025-09-10
Python For Generative Ai Llms written by Thomas D Ullrich and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-10 with Computers categories.
Generative AI has moved from research labs into everyday applications. With the rise of large language models (LLMs), developers now have the tools to build chatbots, translators, summarizers, and intelligent assistants-all with Python. Python for Generative AI & LLMs is a hands-on guide that takes you step by step through installing, running, fine-tuning, and deploying LLMs using Hugging Face Transformers and the latest Python libraries. Written for beginner to intermediate Python developers, this book focuses on practical skills, not heavy theory. Inside you will learn how to: Install Python, Jupyter, Hugging Face Transformers, and Datasets libraries Understand tokens, tokenization, and how models process text Work with pretrained models like GPT, LLaMA, and Falcon Generate text, summaries, translations, and answers with a few lines of code Fine-tune models for custom datasets and tasks Build applications such as chatbots, semantic search, and code generators Deploy your models with FastAPI and manage inference costs Address challenges around token limits, bias, and responsible AI use Every chapter introduces a concept, then follows with working Python code examples and outputs in plain text or tables. No plots or charts are required, making the material accessible and easy to follow. Whether you are a developer entering the AI field, a student exploring NLP, or a professional looking to integrate AI into applications, this book will give you the skills to confidently build and deploy your own Generative AI systems.