Mastering Nlp From Foundations To Llms
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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.
Generative Ai Foundations In Python
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Author : Carlos Rodriguez
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-26
Generative Ai Foundations In Python written by Carlos Rodriguez 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 2024-07-26 with Computers categories.
Begin your generative AI journey with Python as you explore large language models, understand responsible generative AI practices, and apply your knowledge to real-world applications through guided tutorials Key Features Gain expertise in prompt engineering, LLM fine-tuning, and domain adaptation Use transformers-based LLMs and diffusion models to implement AI applications Discover strategies to optimize model performance, address ethical considerations, and build trust in AI systems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe intricacies and breadth of generative AI (GenAI) and large language models can sometimes eclipse their practical application. It is pivotal to understand the foundational concepts needed to implement generative AI. This guide explains the core concepts behind -of-the-art generative models by combining theory and hands-on application. Generative AI Foundations in Python begins by laying a foundational understanding, presenting the fundamentals of generative LLMs and their historical evolution, while also setting the stage for deeper exploration. You’ll also understand how to apply generative LLMs in real-world applications. The book cuts through the complexity and offers actionable guidance on deploying and fine-tuning pre-trained language models with Python. Later, you’ll delve into topics such as task-specific fine-tuning, domain adaptation, prompt engineering, quantitative evaluation, and responsible AI, focusing on how to effectively and responsibly use generative LLMs. By the end of this book, you’ll be well-versed in applying generative AI capabilities to real-world problems, confidently navigating its enormous potential ethically and responsibly.What you will learn Discover the fundamentals of GenAI and its foundations in NLP Dissect foundational generative architectures including GANs, transformers, and diffusion models Find out how to fine-tune LLMs for specific NLP tasks Understand transfer learning and fine-tuning to facilitate domain adaptation, including fields such as finance Explore prompt engineering, including in-context learning, templatization, and rationalization through chain-of-thought and RAG Implement responsible practices with generative LLMs to minimize bias, toxicity, and other harmful outputs Who this book is for This book is for developers, data scientists, and machine learning engineers embarking on projects driven by generative AI. A general understanding of machine learning and deep learning, as well as some proficiency with Python, is expected.
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.
Python Natural Language Processing Cookbook
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Author : Zhenya Antić
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-09-13
Python Natural Language Processing Cookbook written by Zhenya Antić 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 2024-09-13 with Computers categories.
Updated to include three new chapters on transformers, natural language understanding (NLU) with explainable AI, and dabbling with popular LLMs from Hugging Face and OpenAI Key Features Leverage ready-to-use recipes with the latest LLMs, including Mistral, Llama, and OpenAI models Use LLM-powered agents for custom tasks and real-world interactions Gain practical, in-depth knowledge of transformers and their role in implementing various NLP tasks with open-source and advanced LLMs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionHarness the power of Natural Language Processing (NLP) to overcome real-world text analysis challenges with this recipe-based roadmap written by two seasoned NLP experts with vast experience transforming various industries with their NLP prowess. You’ll be able to make the most of the latest NLP advancements, including large language models (LLMs), and leverage their capabilities through Hugging Face transformers. Through a series of hands-on recipes, you’ll master essential techniques such as extracting entities and visualizing text data. The authors will expertly guide you through building pipelines for sentiment analysis, topic modeling, and question-answering using popular libraries like spaCy, Gensim, and NLTK. You’ll also learn to implement RAG pipelines to draw out precise answers from a text corpus using LLMs. This second edition expands your skillset with new chapters on cutting-edge LLMs like GPT-4, Natural Language Understanding (NLU), and Explainable AI (XAI)—fostering trust in your NLP models. By the end of this book, you'll be equipped with the skills to apply advanced text processing techniques, use pre-trained transformer models, build custom NLP pipelines to extract valuable insights from text data to drive informed decision-making.What you will learn Understand fundamental NLP concepts along with their applications using examples in Python Classify text quickly and accurately with rule-based and supervised methods Train NER models and perform sentiment analysis to identify entities and emotions in text Explore topic modeling and text visualization to reveal themes and relationships within text Leverage Hugging Face and OpenAI LLMs to perform advanced NLP tasks Use question-answering techniques to handle both open and closed domains Apply XAI techniques to better understand your model predictions Who this book is for This updated edition of the Python Natural Language Processing Cookbook is for data scientists, machine learning engineers, and developers with a background in Python. Whether you’re looking to learn NLP techniques, extract valuable insights from textual data, or create foundational applications, this book will equip you with basic to intermediate skills. No prior NLP knowledge is necessary to get started. All you need is familiarity with basic programming principles. For seasoned developers, the updated sections offer the latest on transformers, explainable AI, and Generative AI with LLMs.
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.
Apache Spark For Machine Learning
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Author : Deepak Gowda
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-11-01
Apache Spark For Machine Learning written by Deepak Gowda 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 2024-11-01 with Computers categories.
Develop your data science skills with Apache Spark to solve real-world problems for Fortune 500 companies using scalable algorithms on large cloud computing clusters Key Features Apply techniques to analyze big data and uncover valuable insights for machine learning Learn to use cloud computing clusters for training machine learning models on large datasets Discover practical strategies to overcome challenges in model training, deployment, and optimization Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the world of big data, efficiently processing and analyzing massive datasets for machine learning can be a daunting task. Written by Deepak Gowda, a data scientist with over a decade of experience and 30+ patents, this book provides a hands-on guide to mastering Spark’s capabilities for efficient data processing, model building, and optimization. With Deepak’s expertise across industries such as supply chain, cybersecurity, and data center infrastructure, he makes complex concepts easy to follow through detailed recipes. This book takes you through core machine learning concepts, highlighting the advantages of Spark for big data analytics. It covers practical data preprocessing techniques, including feature extraction and transformation, supervised learning methods with detailed chapters on regression and classification, and unsupervised learning through clustering and recommendation systems. You’ll also learn to identify frequent patterns in data and discover effective strategies to deploy and optimize your machine learning models. Each chapter features practical coding examples and real-world applications to equip you with the knowledge and skills needed to tackle complex machine learning tasks. By the end of this book, you’ll be ready to handle big data and create advanced machine learning models with Apache Spark.What you will learn Master Apache Spark for efficient, large-scale data processing and analysis Understand core machine learning concepts and their applications with Spark Implement data preprocessing techniques for feature extraction and transformation Explore supervised learning methods – regression and classification algorithms Apply unsupervised learning for clustering tasks and recommendation systems Discover frequent pattern mining techniques to uncover data trends Who this book is for This book is ideal for data scientists, ML engineers, data engineers, students, and researchers who want to deepen their knowledge of Apache Spark’s tools and algorithms. It’s a must-have for those struggling to scale models for real-world problems and a valuable resource for preparing for interviews at Fortune 500 companies, focusing on large dataset analysis, model training, and deployment.
Essential Guide To Llmops
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Author : RYAN. DOAN
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-31
Essential Guide To Llmops written by RYAN. DOAN 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 2024-07-31 with Computers categories.
Unlock the secrets to mastering LLMOps with innovative approaches to streamline AI workflows, improve model efficiency, and ensure robust scalability, revolutionizing your language model operations from start to finish Key Features Gain a comprehensive understanding of LLMOps, from data handling to model governance Leverage tools for efficient LLM lifecycle management, from development to maintenance Discover real-world examples of industry cutting-edge trends in generative AI operation Purchase of the print or Kindle book includes a free PDF eBook Book Description The rapid advancements in large language models (LLMs) bring significant challenges in deployment, maintenance, and scalability. This Essential Guide to LLMOps provides practical solutions and strategies to overcome these challenges, ensuring seamless integration and the optimization of LLMs in real-world applications. This book takes you through the historical background, core concepts, and essential tools for data analysis, model development, deployment, maintenance, and governance. You’ll learn how to streamline workflows, enhance efficiency in LLMOps processes, employ LLMOps tools for precise model fine-tuning, and address the critical aspects of model review and governance. You’ll also get to grips with the practices and performance considerations that are necessary for the responsible development and deployment of LLMs. The book equips you with insights into model inference, scalability, and continuous improvement, and shows you how to implement these in real-world applications. By the end of this book, you’ll have learned the nuances of LLMOps, including effective deployment strategies, scalability solutions, and continuous improvement techniques, equipping you to stay ahead in the dynamic world of AI. What you will learn Understand the evolution and impact of LLMs in AI Differentiate between LLMOps and traditional MLOps Utilize LLMOps tools for data analysis, preparation, and fine-tuning Master strategies for model development, deployment, and improvement Implement techniques for model inference, serving, and scalability Integrate human-in-the-loop strategies for refining LLM outputs Grasp the forefront of emerging technologies and practices in LLMOps Who this book is for This book is for machine learning professionals, data scientists, ML engineers, and AI leaders interested in LLMOps. It is particularly valuable for those developing, deploying, and managing LLMs, as well as academics and students looking to deepen their understanding of the latest AI and machine learning trends. Professionals in tech companies and research institutions, as well as anyone with foundational knowledge of machine learning will find this resource invaluable for advancing their skills in LLMOps.
Technology Geopolitics And The Transformation Of International Political Economy
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Author : Wongmahesak, Kittisak
language : en
Publisher: IGI Global
Release Date : 2025-07-16
Technology Geopolitics And The Transformation Of International Political Economy written by Wongmahesak, Kittisak and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-16 with Business & Economics categories.
The intersection of technology, geopolitics, and the international political economy (IPE) reshapes the global landscape. As technological advancements like artificial intelligence, quantum computing, and digital currencies evolve, they drive economic change and influence global power dynamics. The rise of tech giants, the competition for technological supremacy, and the growing importance of cybersecurity have introduced new dimensions to traditional geopolitical struggles. These developments challenge established economic systems, disrupt global trade patterns, and redefine the role of states in a highly interconnected and competitive world. As countries navigate this shifting terrain, understanding the complex interplay between technology, geopolitics, and IPE becomes crucial to analyzing both current power structures and future trajectories of global governance. Technology, Geopolitics, and the Transformation of International Political Economy explores the interplay between algorithms, economic structures, and geopolitical power dynamics in the contemporary world. It examines how algorithms and digital technologies reshape global power structures, impact economic relations, and influence the future trajectory of capitalism. This book covers topics such as political science, trade growth, and digital currency, and is a useful resource for economists, business owners, government officials, policymakers, academicians, researchers, and political scientists.
Nlp Llm
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Author : 리오르 가지트
language : ko
Publisher: 한빛미디어
Release Date : 2025-03-10
Nlp Llm written by 리오르 가지트 and has been published by 한빛미디어 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-10 with Computers categories.
LLM 시대의 NLP는 선택이 아닌, 필수! 자연어 처리의 모든 기술을 마스터한다! NLP(자연어 처리)를 마스터하고 싶지만 어디서부터 시작해야 할지 고민인가요? 이 책은 정확하고 올바른 출발점을 제시합니다. 머신러닝과 NLP 분야의 선도자들이 집필한 이 책은 NLP를 깊이 있게 다룹니다. 이 책은 머신러닝의 수학적 기초부터 시작해 LLM과 AI 응용 프로그램 같은 고급 NLP 기술로 점차 나아갑니다. 선형대수학, 최적화, 확률론, 통계학 등 머신러닝과 NLP 알고리즘을 이해하고 구현하는 데 필수적인 기초 개념을 익힐 수 있습니다. 또한 일반적인 머신러닝 기법을 살펴보며, 이를 NLP와 어떻게 연결할 수 있는지도 설명합니다. 이어 텍스트 데이터를 전처리하는 방법, 데이터를 분석하기 위해 정리하고 준비하는 과정 그리고 텍스트 분류를 수행하는 방법을 설명합니다. 이 모든 내용을 파이썬 코드 샘플과 함께 제공합니다. 책의 후반부에서는 LLM의 이론, 설계, 응용과 같은 고급 주제를 심도 있게 논의하며, NLP의 미래 동향에 대한 전문가 의견도 제공합니다. 또한 실제 NLP 비즈니스 사례와 솔루션을 통해 실무 능력을 키울 수 있도록 도와줍니다.
Mastering Generative Ai And Llms
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Author : Guillaume Lessard
language : en
Publisher: iD01t Productions
Release Date : 2024-12-15
Mastering Generative Ai And Llms written by Guillaume Lessard and has been published by iD01t Productions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-15 with Computers categories.
Mastering Generative AI and LLMs: The Definitive Guide to Transformative Technologies By Guillaume Lessard Unlock the full potential of Generative AI and Large Language Models (LLMs) with this comprehensive and practical guide. Mastering Generative AI and LLMs takes you on an in-depth journey into the cutting-edge world of artificial intelligence, from foundational concepts to advanced applications. Whether you are a developer, researcher, entrepreneur, or enthusiast, this book offers everything you need to understand, build, and implement AI-powered solutions. Learn how to harness the creative power of Generative AI to transform industries, solve complex problems, and create groundbreaking innovations. What You’ll Learn The Evolution of AI: Discover how neural networks, machine learning, and deep learning paved the way for Generative AI breakthroughs. Core Technologies Behind LLMs: Understand tokenization, attention mechanisms, and the transformative impact of architectures like GPT and BERT. Building Generative Models: A hands-on approach to creating models like GANs, training with high-quality datasets, and optimizing for real-world use. Advanced Customizations: Explore techniques like Transfer Learning, Reinforcement Learning with Human Feedback (RLHF), and integrating external knowledge to enhance LLMs. Open-Source Tools: Leverage open-source models such as GPT-Neo and Stable Diffusion to power your AI projects. Real-World Applications Learn how Generative AI is revolutionizing industries: Healthcare: Accelerate drug discovery with AI-generated molecular structures. Retail: Automate product descriptions and create personalized shopping experiences. Entertainment: Craft scripts, visual effects, and content tailored to user preferences. Hands-On Projects Dive into practical exercises, including: Building a conversational chatbot using GPT-4 APIs. Fine-tuning Stable Diffusion to generate custom art. Deploying generative models on the cloud with platforms like AWS. Why This Book? Packed with detailed case studies, technical explanations, and ethical considerations, this book is more than a technical manual—it’s a roadmap for shaping the future of AI responsibly. Guillaume Lessard combines expertise with accessibility, making advanced AI concepts approachable for all audiences. Step into the future of AI innovation. Mastering Generative AI and LLMs is your ultimate guide to unlocking the transformative power of artificial intelligence. Available Now!