Quick Start Guide To Large Language Models
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Quick Start Guide To Large Language Models
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Author : Sinan Ozdemir
language : en
Publisher: Addison-Wesley Professional
Release Date : 2023-09-20
Quick Start Guide To Large Language Models written by Sinan Ozdemir and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-20 with Computers categories.
The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like ChatGPT are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them. In Quick Start Guide to Large Language Models, pioneering data scientist and AI entrepreneur Sinan Ozdemir clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems. Ozdemir brings together all you need to get started, even if you have no direct experience with LLMs: step-by-step instructions, best practices, real-world case studies, hands-on exercises, and more. Along the way, he shares insights into LLMs' inner workings to help you optimize model choice, data formats, parameters, and performance. You'll find even more resources on the companion website, including sample datasets and code for working with open- and closed-source LLMs such as those from OpenAI (GPT-4 and ChatGPT), Google (BERT, T5, and Bard), EleutherAI (GPT-J and GPT-Neo), Cohere (the Command family), and Meta (BART and the LLaMA family). Learn key concepts: pre-training, transfer learning, fine-tuning, attention, embeddings, tokenization, and more Use APIs and Python to fine-tune and customize LLMs for your requirements Build a complete neural/semantic information retrieval system and attach to conversational LLMs for retrieval-augmented generation Master advanced prompt engineering techniques like output structuring, chain-ofthought, and semantic few-shot prompting Customize LLM embeddings to build a complete recommendation engine from scratch with user data Construct and fine-tune multimodal Transformer architectures using opensource LLMs Align LLMs using Reinforcement Learning from Human and AI Feedback (RLHF/RLAIF) Deploy prompts and custom fine-tuned LLMs to the cloud with scalability and evaluation pipelines in mind "By balancing the potential of both open- and closed-source models, Quick Start Guide to Large Language Models stands as a comprehensive guide to understanding and using LLMs, bridging the gap between theoretical concepts and practical application." --Giada Pistilli, Principal Ethicist at HuggingFace "A refreshing and inspiring resource. Jam-packed with practical guidance and clear explanations that leave you smarter about this incredible new field." --Pete Huang, author of The Neuron Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Transforming Conversational Ai
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Author : Michael McTear
language : en
Publisher: Springer Nature
Release Date : 2024-02-24
Transforming Conversational Ai written by Michael McTear and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-24 with Business & Economics categories.
Acquire the knowledge needed to work effectively in conversational artificial intelligence (AI) and understand the opportunities and threats it can potentially bring. This book will help you navigate from the traditional world of dialogue systems that revolve around hard coded scripts, to the world of large language models, prompt engineering, conversational AI platforms, multi-modality, and ultimately autonomous agents. In this new world, decisions are made by a system that may forever remain a ‘black box’ for most of us. This book aims to eliminate unnecessary noise and describe the fundamental components of conversational AI. Past experiences will prove invaluable in constructing seamless hybrid systems. This book will provide the most recommended solutions, recognizing that it is not always necessary to blindly pursue new tools. Written in unprecedented and turbulent times for conversational interfaces you’ll see that despite previous waves of advancement in conversational technology, now conversational interfaces are gaining unparalleled popularity. Specifically, the release of ChatGPT in November 2022 by Open AI revolutionized the conversational paradigm and showed how easy and intuitive communication with a computer can be. Old professions are being disrupted, new professions are emerging, and even the most conservative corporations are changing their strategy and experimenting with large language models, allocating an unprecedented amount of budget to these projects. No one knows for sure the exact future of conversational AI, but everyone agrees that it’s here to stay. What You'll Learn See how large language models are constructed and used in conversational systems Review the risks and challenges of new technologies in conversational AI Examine techniques for prompt engineering Enable practitioners to keep abreast of recent developments in conversational AI Who This Book Is For Conversation designers, product owners, and product or project managers in conversational AI who wish to learn about new methods and challenges posed by the recent emergence in the public domain of ChatGPT. Data scientists, final year undergraduates and graduates of computer science
Building Personality Driven Language Models
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Author : Karol Przystalski
language : en
Publisher: Springer Nature
Release Date : 2025-03-22
Building Personality Driven Language Models written by Karol Przystalski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-22 with Computers categories.
This book provides an innovative exploration into the realm of artificial intelligence (AI) by developing personalities for large language models (LLMs) using psychological principles. Aimed at making AI interactions feel more human-like, the book guides you through the process of applying psychological assessments to AIs, enabling them to exhibit traits such as extraversion, openness, and emotional stability. Perfect for developers, researchers, and entrepreneurs, this work merges psychology, philosophy, business, and cutting-edge computing to enhance how AIs understand and engage with humans across various industries like gaming and healthcare. The book not only unpacks the theoretical aspects of these advancements but also equips you with practical coding exercises and Python code examples, helping you create AI systems that are both innovative and relatable. Whether you’re looking to deepen your understanding of AI personalities or integrate them into commercial applications, this book offers the tools and insights needed to pioneer this exciting frontier.
Handbook Of Chinese Language Learning And Technology
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Author : Shou-Hsin Teng
language : en
Publisher: Springer Nature
Release Date : 2025-02-25
Handbook Of Chinese Language Learning And Technology written by Shou-Hsin Teng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-25 with Education categories.
This handbook explores quantitative linguistics, pedagogy, and Mandarin language acquisition in an integrated fashion and helps readers grasp how insights from quantitative linguistics can shed light on Mandarin language acquisition. It focuses on issues related to language processing, learning, and teaching and how these aspects are affected or enhanced by corpus-based and computational linguistics. By following a data-driven approach, the handbook demonstrates how theoretical problems in the acquisition of Chinese can be resolved with empirical evidence. The book serves as an essential resource for students and researchers wishing to explore the fascinating field of Chinese language processing and acquisition.
Generative Ai And Llms
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Author : S. Balasubramaniam
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-09-23
Generative Ai And Llms written by S. Balasubramaniam and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-23 with Computers categories.
Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary objective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative artificial intelligence (AI) stands out due to its unique characteristic of undergoing development and maturation in a highly transparent manner, with its progress being observed by the public at large. The current era of artificial intelligence is being influenced by the imperative to effectively utilise its capabilities in order to enhance corporate operations. Specifically, the use of large language model (LLM) capabilities, which fall under the category of Generative AI, holds the potential to redefine the limits of innovation and productivity. However, as firms strive to include new technologies, there is a potential for compromising data privacy, long-term competitiveness, and environmental sustainability. This book delves into the exploration of generative artificial intelligence (GAI) and LLM. It examines the historical and evolutionary development of generative AI models, as well as the challenges and issues that have emerged from these models and LLM. This book also discusses the necessity of generative AI-based systems and explores the various training methods that have been developed for generative AI models, including LLM pretraining, LLM fine-tuning, and reinforcement learning from human feedback. Additionally, it explores the potential use cases, applications, and ethical considerations associated with these models. This book concludes by discussing future directions in generative AI and presenting various case studies that highlight the applications of generative AI and LLM.
Natural Language Analytics With Generative Large Language Models
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Author : Francisco S. Marcondes
language : en
Publisher: Springer Nature
Release Date : 2025-02-13
Natural Language Analytics With Generative Large Language Models written by Francisco S. Marcondes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-13 with Computers categories.
This book explores the application of generative Large Language Models (LLMs) for extracting and analyzing data from natural language artefacts. Unlike traditional uses of LLMs, such as translation and summarization, this book focuses on utilizing these models to convert unstructured text into data that can be processed through the data science pipeline to generate actionable insights. The content is designed for professionals in diverse fields including cognitive science, linguistics, management, and information systems. It combines insights from both industry and academia to provide a comprehensive understanding of how LLMs can be effectively used for natural language analytics (NLA). The book details practical methodologies for implementing LLMs locally using open-source tools, ensuring data privacy and feasibility without the need for expensive infrastructure. Key topics include interpretant, mindset and cultural analysis, emphasizing the use of LLMs to derive soft data—qualitative information crucial for nuanced decision-making. The text also outlines the technical aspects of LLMs, including their architecture, token embeddings, and the differences between encoder-based and decoder-based models. By providing a case study and practical examples, the authors show how LLMs can be used to meet various analytical needs, making this book a valuable resource for anyone looking to integrate advanced natural language processing techniques into their data analysis workflows.
Natural Language Processing With Python Quick Start Guide
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Author : Nirant Kasliwal
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-30
Natural Language Processing With Python Quick Start Guide written by Nirant Kasliwal 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 2018-11-30 with Computers categories.
Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learning Key FeaturesA no-math, code-driven programmer’s guide to text processing and NLPGet state of the art results with modern tooling across linguistics, text vectors and machine learningFundamentals of NLP methods from spaCy, gensim, scikit-learn and PyTorchBook Description NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP. The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a workflow for building NLP applications. We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn. We conclude by deploying these models as REST APIs with Flask. By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges. What you will learnUnderstand classical linguistics in using English grammar for automatically generating questions and answers from a free text corpusWork with text embedding models for dense number representations of words, subwords and characters in the English language for exploring document clusteringDeep Learning in NLP using PyTorch with a code-driven introduction to PyTorchUsing an NLP project management Framework for estimating timelines and organizing your project into stagesHack and build a simple chatbot application in 30 minutesDeploy an NLP or machine learning application using Flask as RESTFUL APIsWho this book is for Programmers who wish to build systems that can interpret language. Exposure to Python programming is required. Familiarity with NLP or machine learning vocabulary will be helpful, but not mandatory.
The Role Of Generative Ai In The Communication Classroom
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Author : Elmoudden, Sanae
language : en
Publisher: IGI Global
Release Date : 2024-02-12
The Role Of Generative Ai In The Communication Classroom written by Elmoudden, Sanae and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-12 with Education categories.
In an era marked by the rapid integration of Artificial Intelligence (AI) into our lives, the discourse surrounding its implications has intensified. The Role of Generative AI in the Communication Classroom is a pioneering book that delves into the multifaceted dimensions of AI, specifically focusing on OpenAI's revolutionary Chat Generative Pre-Trained Transformer (Chat GPT) and its profound influence on the landscape of communication education. This book navigates the intersection of technology, education, and ethics, shedding light on the imperative need for a collaborative approach to shape AI's evolution. AI's potential to reshape industries and human roles is undeniable. Rooted in the intricate workings of AI and its hallmark, Chat GPT, this book meticulously dissects the dynamic relationship between humans and machines. The discourse extends beyond technology and into the realm of education, asserting that the power to mold AI's trajectory cannot rest solely in the hands of developers. While revealing AI's transformative potential in the communication classroom, the book conscientiously explores ethical concerns and biases, fostering a balanced approach to its integration. This book is instrumental to the ongoing discourse on AI's role in education. The call for ethical considerations, inclusivity, and regulation serves as a guiding compass for educators, students, developers, and policymakers alike. The book ensures a holistic perspective on AI's integration by addressing privacy, citation, voice ownership, and overall digital ethics.
Innovative Methods In Korean Language Teaching
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Author : Nicola Fraschini
language : en
Publisher: Taylor & Francis
Release Date : 2024-12-30
Innovative Methods In Korean Language Teaching written by Nicola Fraschini and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Foreign Language Study categories.
Innovative Methods in Korean Language Teaching showcases research-based and experience-based contributions and reflections on the potential of adopting technological and non-technological innovations to promote Korean language students’ learning. The chapters included in this book consider a wide range of innovative technologies and approaches, such as large language models, virtual reality solutions, metaverse platforms, multimodal teaching, and critical pedagogy, and represent a variety of geographical learning contexts from North America to Europe, from Korea to the broader Asia-Pacific region. Overall, these contributions make the case for embracing new technologies instead of banning them and for accepting pedagogical shifts that take into consideration contemporary understandings of the communication, teaching, and learning processes. This book will be of interest to graduate students, researchers, and practitioners of Korean language education and to those working on language teaching and learning in general, to inform future teaching practices through careful consideration of contemporary technologies and teaching approaches.
Academic Integrity In The Age Of Artificial Intelligence
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Author : Mahmud, Saadia
language : en
Publisher: IGI Global
Release Date : 2024-02-13
Academic Integrity In The Age Of Artificial Intelligence written by Mahmud, Saadia and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-13 with Education categories.
Powerful generative Artificial Intelligence (AI) has defined and transformed our modern era, and the fundamental conceptualization of academia stands at a crossroads. Academic Integrity in the Age of Artificial Intelligence delves deep into the seismic shifts and intricate challenges brought forth by the proliferation of AI technologies, exploring the intricacies between innovation and integrity. The rise of generative AI, exemplified by ChatGPT, has set a cascade of change across diverse sectors, including higher education, medicine, and the arts. This book dissects the multifaceted impact of AI on the academic landscape. With AI's ability to craft text and imagery mirroring human creativity, the lines between authentic scholarship and synthetic deception blur. The book examines the delicate balance between productivity and ethics while weaving a comprehensive tapestry of insights from various stakeholders. From academics grappling with the definition of AI-assisted breaches of academic integrity to policymakers reshaping the future of higher education, this book engages a myriad of voices. It scrutinizes the nascent challenges in assessment design, the urgent need to update antiquated integrity policies, and the importance of research ethics in an AI-driven world. This book is ideal for educators, policymakers, students, and technologists through the complicated terrain of AI ethics.