Mastering Nlp With Large Language Models
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Mastering Large Language Models
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Author : Sanket Subhash Khandare
language : en
Publisher: BPB Publications
Release Date : 2024-03-12
Mastering Large Language Models written by Sanket Subhash Khandare and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-12 with Computers categories.
Do not just talk AI, build it: Your guide to LLM application development KEY FEATURES ● Explore NLP basics and LLM fundamentals, including essentials, challenges, and model types. ● Learn data handling and pre-processing techniques for efficient data management. ● Understand neural networks overview, including NN basics, RNNs, CNNs, and transformers. ● Strategies and examples for harnessing LLMs. DESCRIPTION Transform your business landscape with the formidable prowess of large language models (LLMs). The book provides you with practical insights, guiding you through conceiving, designing, and implementing impactful LLM-driven applications. This book explores NLP fundamentals like applications, evolution, components and language models. It teaches data pre-processing, neural networks , and specific architectures like RNNs, CNNs, and transformers. It tackles training challenges, advanced techniques such as GANs, meta-learning, and introduces top LLM models like GPT-3 and BERT. It also covers prompt engineering. Finally, it showcases LLM applications and emphasizes responsible development and deployment. With this book as your compass, you will navigate the ever-evolving landscape of LLM technology, staying ahead of the curve with the latest advancements and industry best practices. WHAT YOU WILL LEARN ● Grasp fundamentals of natural language processing (NLP) applications. ● Explore advanced architectures like transformers and their applications. ● Master techniques for training large language models effectively. ● Implement advanced strategies, such as meta-learning and self-supervised learning. ● Learn practical steps to build custom language model applications. WHO THIS BOOK IS FOR This book is tailored for those aiming to master large language models, including seasoned researchers, data scientists, developers, and practitioners in natural language processing (NLP). TABLE OF CONTENTS 1. Fundamentals of Natural Language Processing 2. Introduction to Language Models 3. Data Collection and Pre-processing for Language Modeling 4. Neural Networks in Language Modeling 5. Neural Network Architectures for Language Modeling 6. Transformer-based Models for Language Modeling 7. Training Large Language Models 8. Advanced Techniques for Language Modeling 9. Top Large Language Models 10. Building First LLM App 11. Applications of LLMs 12. Ethical Considerations 13. Prompt Engineering 14. Future of LLMs and Its Impact
Mastering Large Language Models With Python Unleash The Power Of Advanced Natural Language Processing For Enterprise Innovation And Efficiency Using Large Language Models Llms With Python
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Author : Raj Arun
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-04-12
Mastering Large Language Models With Python Unleash The Power Of Advanced Natural Language Processing For Enterprise Innovation And Efficiency Using Large Language Models Llms With Python written by Raj Arun and has been published by Orange Education Pvt Limited 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. Book 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 you will 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. 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
Mastering Nlp From Foundations To Llms
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Author : Lior Gazit
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-04-26
Mastering Nlp From Foundations To Llms written by Lior Gazit 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 2024-04-26 with Computers categories.
Enhance your NLP proficiency with modern frameworks like LangChain, explore mathematical foundations and code samples, and gain expert insights into current and future trends Key Features Learn how to build Python-driven solutions with a focus on NLP, LLMs, RAGs, and GPT Master embedding techniques and machine learning principles for real-world applications Understand the mathematical foundations of NLP and deep learning designs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDo you want to master Natural Language Processing (NLP) but don’t know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you’ll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You’ll also explore general machine learning techniques and find out how they relate to NLP. Next, you’ll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You’ll get all of this and more along with complete Python code samples. By the end of the book, the advanced topics of LLMs’ theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You’ll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.What you will learn Master the mathematical foundations of machine learning and NLP Implement advanced techniques for preprocessing text data and analysis Design ML-NLP systems in Python Model and classify text using traditional machine learning and deep learning methods Understand the theory and design of LLMs and their implementation for various applications in AI Explore NLP insights, trends, and expert opinions on its future direction and potential Who this book is for This book is for deep learning and machine learning researchers, NLP practitioners, ML/NLP educators, and STEM students. Professionals working with text data as part of their projects will also find plenty of useful information in this book. Beginner-level familiarity with machine learning and a basic working knowledge of Python will help you get the best out of this book.
Mastering Nlp With Large Language Models
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Author : Sylvester Holmes
language : en
Publisher: Independently Published
Release Date : 2025-06-04
Mastering Nlp With Large Language Models written by Sylvester Holmes and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-04 with Computers categories.
Mastering NLP with Large Language Models: A Practical Guide to Modern AI Unlock the power of cutting-edge Natural Language Processing with this hands-on guide to building intelligent systems using Large Language Models (LLMs). Mastering NLP with Large Language Models walks you through the core techniques, tools, and real-world applications that define today's most advanced AI workflows. Whether you're building chatbots, search engines, or autonomous agents, this book offers a clear, structured path to understanding and deploying LLMs effectively. Covering everything from transformer basics to Retrieval-Augmented Generation (RAG), prompt engineering, multimodal models, and ethical deployment, this guide bridges theory with practical implementation. You'll gain deep insights into tools like Hugging Face Transformers, LangChain, Haystack, OpenAI APIs, Cohere, and more-while learning how to optimize, scale, and deploy AI systems with confidence. This book is a comprehensive, step-by-step resource for mastering NLP with LLMs. It's structured to take you from foundational concepts through to building production-ready applications. With fully functional code examples in Python, you'll learn to fine-tune models, integrate vector databases, apply efficient training methods like LoRA and adapters, and explore deployment with tools like FastAPI and Streamlit. Key Features of this Book: In-depth coverage of Large Language Models, including GPT, BERT, and multimodal architectures Practical projects using Hugging Face, LangChain, Haystack, OpenAI, and Cohere Tutorials on RAG pipelines, prompt tuning, quantization, and distillation Deployment strategies with FastAPI, Streamlit, and MLOps practices Discussions on bias, fairness, transparency, and AI governance Easy-to-follow Python code with real-world use cases This book is ideal for data scientists, machine learning engineers, software developers, AI researchers, and tech professionals eager to master NLP with large language models. It's also a solid resource for advanced learners, students, and educators seeking modern, practical insights into applied AI. Ready to build the future of AI with the most powerful NLP tools available today? Grab your copy of Mastering NLP with Large Language Models: A Practical Guide to Modern AI and start developing intelligent, scalable, and responsible AI systems-one project at a time.
Mastering Natural Language Processing
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Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date :
Mastering Natural Language Processing written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Unveil the Secrets of Language Understanding and Generation In the realm of artificial intelligence and communication, Natural Language Processing (NLP) stands as a transformative force that bridges the gap between humans and machines. "Mastering Natural Language Processing" is your definitive guide to comprehending and harnessing the potential of this dynamic field, empowering you to create intelligent language-based applications with precision. About the Book: As technology evolves, the ability to understand and generate human language becomes increasingly essential. "Mastering Natural Language Processing" offers a comprehensive exploration of NLP—a crucial discipline in the world of AI and communication. This book caters to both beginners and experienced learners aiming to excel in NLP concepts, techniques, and applications. Key Features: NLP Fundamentals: Begin by understanding the core principles of Natural Language Processing. Learn about linguistic concepts, tokenization, and language models. Text Classification and Sentiment Analysis: Dive into text analysis techniques. Explore methods for classifying text and determining sentiment, enabling you to understand user opinions and emotions. Named Entity Recognition: Grasp the art of identifying entities in text. Understand how to extract names, places, dates, and other crucial information from unstructured data. Language Generation: Explore techniques for generating human-like language. Learn how to create chatbots, language models, and automated content. Machine Translation: Understand the significance of machine translation. Learn how to build systems that translate text between languages with accuracy. Speech Recognition: Delve into the realm of speech recognition. Explore techniques for converting spoken language into text, enabling voice interfaces and transcription. Question Answering Systems: Grasp the power of question-answering systems. Learn how to build applications that provide answers to user questions based on available data. Real-World Applications: Gain insights into how NLP is applied across industries. From customer service to healthcare, discover the diverse applications of natural language processing. Why This Book Matters: In an age of communication and interaction, mastering NLP offers a competitive advantage. "Mastering Natural Language Processing" empowers data scientists, developers, and technology enthusiasts to leverage NLP concepts, enabling them to create intelligent language-based applications that enhance user experiences and drive innovation. Revolutionize Communication with AI: In the landscape of artificial intelligence, Natural Language Processing is transforming how humans and machines interact. "Mastering Natural Language Processing" equips you with the knowledge needed to leverage NLP concepts, enabling you to create intelligent language-based applications that bridge communication gaps and redefine possibilities. Whether you're a seasoned practitioner or new to the world of NLP, this book will guide you in building a solid foundation for effective language-based solutions. Your journey to mastering Natural Language Processing starts here. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
Mastering Large Language Models With Python
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Author : Raj Arun R
language : en
Publisher: Sextil Online LLC
Release Date : 2024-04-12
Mastering Large Language Models With Python written by Raj Arun R and has been published by Sextil Online LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-12 with Computers categories.
“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.
Mastering Transformers
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Author : Savaş Yıldırım
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-03
Mastering Transformers written by Savaş Yıldırım 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 2024-06-03 with Computers categories.
Explore transformer-based language models from BERT to GPT, delving into NLP and computer vision tasks, while tackling challenges effectively Key Features Understand the complexity of deep learning architecture and transformers architecture Create solutions to industrial natural language processing (NLP) and computer vision (CV) problems Explore challenges in the preparation process, such as problem and language-specific dataset transformation Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionTransformer-based language models such as BERT, T5, GPT, DALL-E, and ChatGPT have dominated NLP studies and become a new paradigm. Thanks to their accurate and fast fine-tuning capabilities, transformer-based language models have been able to outperform traditional machine learning-based approaches for many challenging natural language understanding (NLU) problems. Aside from NLP, a fast-growing area in multimodal learning and generative AI has recently been established, showing promising results. Mastering Transformers will help you understand and implement multimodal solutions, including text-to-image. Computer vision solutions that are based on transformers are also explained in the book. You’ll get started by understanding various transformer models before learning how to train different autoregressive language models such as GPT and XLNet. The book will also get you up to speed with boosting model performance, as well as tracking model training using the TensorBoard toolkit. In the later chapters, you’ll focus on using vision transformers to solve computer vision problems. Finally, you’ll discover how to harness the power of transformers to model time series data and for predicting. By the end of this transformers book, you’ll have an understanding of transformer models and how to use them to solve challenges in NLP and CV.What you will learn Focus on solving simple-to-complex NLP problems with Python Discover how to solve classification/regression problems with traditional NLP approaches Train a language model and explore how to fine-tune models to the downstream tasks Understand how to use transformers for generative AI and computer vision tasks Build transformer-based NLP apps with the Python transformers library Focus on language generation such as machine translation and conversational AI in any language Speed up transformer model inference to reduce latency Who this book is for This book is for deep learning researchers, hands-on practitioners, and ML/NLP researchers. Educators, as well as students who have a good command of programming subjects, knowledge in the field of machine learning and artificial intelligence, and who want to develop apps in the field of NLP as well as multimodal tasks will also benefit from this book’s hands-on approach. Knowledge of Python (or any programming language) and machine learning literature, as well as a basic understanding of computer science, are required.
Decoding Large Language Models
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Author : Irena Cronin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-10-31
Decoding Large Language Models written by Irena Cronin 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 2024-10-31 with Computers categories.
Explore the architecture, development, and deployment strategies of large language models to unlock their full potential Key Features Gain in-depth insight into LLMs, from architecture through to deployment Learn through practical insights into real-world case studies and optimization techniques Get a detailed overview of the AI landscape to tackle a wide variety of AI and NLP challenges Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionEver wondered how large language models (LLMs) work and how they're shaping the future of artificial intelligence? Written by a renowned author and AI, AR, and data expert, Decoding Large Language Models is a combination of deep technical insights and practical use cases that not only demystifies complex AI concepts, but also guides you through the implementation and optimization of LLMs for real-world applications. You’ll learn about the structure of LLMs, how they're developed, and how to utilize them in various ways. The chapters will help you explore strategies for improving these models and testing them to ensure effective deployment. Packed with real-life examples, this book covers ethical considerations, offering a balanced perspective on their societal impact. You’ll be able to leverage and fine-tune LLMs for optimal performance with the help of detailed explanations. You’ll also master techniques for training, deploying, and scaling models to be able to overcome complex data challenges with confidence and precision. This book will prepare you for future challenges in the ever-evolving fields of AI and NLP. By the end of this book, you’ll have gained a solid understanding of the architecture, development, applications, and ethical use of LLMs and be up to date with emerging trends, such as GPT-5.What you will learn Explore the architecture and components of contemporary LLMs Examine how LLMs reach decisions and navigate their decision-making process Implement and oversee LLMs effectively within your organization Master dataset preparation and the training process for LLMs Hone your skills in fine-tuning LLMs for targeted NLP tasks Formulate strategies for the thorough testing and evaluation of LLMs Discover the challenges associated with deploying LLMs in production environments Develop effective strategies for integrating LLMs into existing systems Who this book is for If you’re a technical leader working in NLP, an AI researcher, or a software developer interested in building AI-powered applications, this book is for you. To get the most out of this book, you should have a foundational understanding of machine learning principles; proficiency in a programming language such as Python; knowledge of algebra and statistics; and familiarity with natural language processing basics.
Mastering Spacy
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Author : Déborah Mesquita
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-02-14
Mastering Spacy written by Déborah Mesquita 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 2025-02-14 with Computers categories.
Discover how to master advanced spaCy techniques, including custom pipelines, LLM integration, and model training, to build NLP solutions efficiently and effectively Key Features Build End-to-End NLP Workflows, From Local Development to Production with Weasel and FastAPI Master No-Training NLP Development with spaCy-LLM, From Prompt Engineering to Custom Tasks Create Advanced NLP Solutions, From Custom Components to Neural Coreference Resolution Book Description Mastering spaCy, Second Edition is your comprehensive guide to building sophisticated NLP applications using the spaCy ecosystem. This revised edition embraces the latest advancements in NLP, featuring new chapters on Large Language Models with spaCy-LLM, transformers integration, and end-to-end workflow management with Weasel. With this new edition you’ll learn to enhance NLP tasks using LLMs with spaCy-llm, manage end-to-end workflows using Weasel and integrating spaCy with third-party libraries like Streamlit, FastAPI, and DVC. From training custom named entity recognition (NER) pipelines to categorizing emotions in Reddit posts, readers will explore advanced topics like text classification and coreference resolution. This book takes you on a journey through spaCy’s capabilities, starting with the fundamentals of NLP, such as tokenization, named entity recognition, and dependency parsing. As you progress, you’ll delve into advanced topics like creating custom components, training domain-specific models, and building scalable NLP workflows. By end of the book, through practical examples, clear explanations, tips and tricks you will be empowered to build robust NLP pipelines and integrate them with web applications to build end-to-end solutions. What will you learn Apply transformer models and fine-tune them for specialized NLP tasks Master spaCy core functionalities including data structures and processing pipelines Develop custom pipeline components and semantic extractors for domain-specific needs Build scalable applications by integrating spaCy with FastAPI, Streamlit, and DVC Master advanced spaCy features including coreference resolution and neural pipeline components Train domain-specific models, including NER and coreference resolution Prototype rapidly with spaCy-LLM and develop custom LLM tasks Who this book is for This book is tailored for NLP engineers, machine learning developers, and LLM engineers looking to build production-grade language processing solutions. While primarily targeting professionals working with language models and NLP pipelines, it's also valuable for software engineers transitioning into NLP development. Basic Python programming knowledge and familiarity with NLP concepts is recommended to leverage spaCy's latest capabilities.
Machine Learning Mastery Deep Learning And Natural Language Processing Integration
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Author : Dr.Talluri.Sunil Kumar
language : en
Publisher: SK Research Group of Companies
Release Date : 2024-07-24
Machine Learning Mastery Deep Learning And Natural Language Processing Integration written by Dr.Talluri.Sunil Kumar and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Computers categories.
Dr.Talluri.Sunil Kumar, Professor, Department of CSE-(CyS, DS) and AI&DS, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India. Dr.Sagar Yeruva, Associate Professor, Department of CSE - AIML & IoT, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India.