Edward A. Fox – författare

Electronic Theses and Dissertations examines how electronic publication of theses and dissertations might enhance graduate education. This text clarifies the composition, evaluation, dissemination, and preservation of electronic theses and dissertations (ETDs), and provides a conceptual framework for the development of effective ETD programs. It identifies the main technical concerns related to the adoption of ETD initiatives and contains answers and methods that have proven effective in the longest-running library-group support effort for campus ETDs, making it the foremost guide to the latest innovations, practices, and policies in ETD production, distribution, and institutionalization.

Electronic Theses and Dissertations examines how electronic publication of theses and dissertations might enhance graduate education. This text clarifies the composition, evaluation, dissemination, and preservation of electronic theses and dissertations (ETDs), and provides a conceptual framework for the development of effective ETD programs. It identifies the main technical concerns related to the adoption of ETD initiatives and contains answers and methods that have proven effective in the longest-running library-group support effort for campus ETDs, making it the foremost guide to the latest innovations, practices, and policies in ETD production, distribution, and institutionalization.

Updated to include three new chapters on transformers, natural language understanding (NLU) with explainable AI, and dabbling with popular LLMs from Hugging Face and OpenAIKey FeaturesLeverage ready-to-use recipes with the latest LLMs, including Mistral, Llama, and OpenAI modelsUse LLM-powered agents for custom tasks and real-world interactionsGain practical, in-depth knowledge of transformers and their role in implementing various NLP tasks with open-source and advanced LLMsPurchase of the print or Kindle book includes a free PDF eBookBook 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 learnUnderstand fundamental NLP concepts along with their applications using examples in PythonClassify text quickly and accurately with rule-based and supervised methodsTrain NER models and perform sentiment analysis to identify entities and emotions in textExplore topic modeling and text visualization to reveal themes and relationships within textLeverage Hugging Face and OpenAI LLMs to perform advanced NLP tasksUse question-answering techniques to handle both open and closed domainsApply XAI techniques to better understand your model predictionsWho this book is forThis 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.

While the first book adopts a minimalist and formal approach to DLs, and provides a systematic and functional method to design and implement DL exploring services, here we broaden to practical DLs with richer metamodels, demonstrating the power of 5S for integration and evaluation.

Digital libraries (DLs) have evolved since their launch in 1991 into an important type of information system, with widespread application.

Digital libraries (DLs) have introduced new technologies, as well as leveraging, enhancing, and integrating related technologies, since the early 1990s. We hope this book will help show how formal approaches can enhance the development of suitable technologies and how they can be better integrated with DLs and other information systems.