Knowledge-augmented Methods for Natural Language Processing PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Knowledge-augmented Methods for Natural Language Processing PDF full book. Access full book title Knowledge-augmented Methods for Natural Language Processing by Meng Jiang. Download full books in PDF and EPUB format.
Author: Meng Jiang
Publisher: Springer Nature
ISBN: 9819707471
Category :
Languages : en
Pages : 101
Get Book Here
Book Description
Author: Meng Jiang
Publisher: Springer Nature
ISBN: 9819707471
Category :
Languages : en
Pages : 101
Get Book Here
Book Description
Author: Wenhao Yu
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Author: Jacob Eisenstein
Publisher: MIT Press
ISBN: 0262042843
Category : Computers
Languages : en
Pages : 535
Get Book Here
Book Description
A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
Author: Denis Rothman
Publisher: Packt Publishing Ltd
ISBN: 1805123742
Category : Computers
Languages : en
Pages : 731
Get Book Here
Book Description
The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal Generative AI, risks, and implementations with ChatGPT Plus with GPT-4, Hugging Face, and Vertex AI Key Features Compare and contrast 20+ models (including GPT-4, BERT, and Llama 2) and multiple platforms and libraries to find the right solution for your project Apply RAG with LLMs using customized texts and embeddings Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases Purchase of the print or Kindle book includes a free eBook in PDF format Book DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, applications, and various platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV). The book guides you through different transformer architectures to the latest Foundation Models and Generative AI. You’ll pretrain and fine-tune LLMs and work through different use cases, from summarization to implementing question-answering systems with embedding-based search techniques. You will also learn the risks of LLMs, from hallucinations and memorization to privacy, and how to mitigate such risks using moderation models with rule and knowledge bases. You’ll implement Retrieval Augmented Generation (RAG) with LLMs to improve the accuracy of your models and gain greater control over LLM outputs. Dive into generative vision transformers and multimodal model architectures and build applications, such as image and video-to-text classifiers. Go further by combining different models and platforms and learning about AI agent replication. This book provides you with an understanding of transformer architectures, pretraining, fine-tuning, LLM use cases, and best practices.What you will learn Breakdown and understand the architectures of the Original Transformer, BERT, GPT models, T5, PaLM, ViT, CLIP, and DALL-E Fine-tune BERT, GPT, and PaLM 2 models Learn about different tokenizers and the best practices for preprocessing language data Pretrain a RoBERTa model from scratch Implement retrieval augmented generation and rules bases to mitigate hallucinations Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP Go in-depth into vision transformers with CLIP, DALL-E 2, DALL-E 3, and GPT-4V Who this book is for This book is ideal for NLP and CV engineers, software developers, data scientists, machine learning engineers, and technical leaders looking to advance their LLMs and generative AI skills or explore the latest trends in the field. Knowledge of Python and machine learning concepts is required to fully understand the use cases and code examples. However, with examples using LLM user interfaces, prompt engineering, and no-code model building, this book is great for anyone curious about the AI revolution.
Author: Anand Vemula
Publisher: Anand Vemula
ISBN:
Category : Computers
Languages : en
Pages : 42
Get Book Here
Book Description
"From Concept to Creation: Retrieval-Augmented Generation (RAG) Handbook" serves as a comprehensive guide for both novices and experts delving into the realm of advanced generative AI. This handbook demystifies the intricate process of Retrieval-Augmented Generation (RAG), offering practical insights and techniques to harness its full potential. The book begins by laying a solid foundation, elucidating the underlying principles of RAG technology and its significance in the landscape of artificial intelligence and storytelling. Readers are introduced to the fusion of retrieval-based methods with generative models, unlocking a new paradigm for crafting compelling narratives. As readers progress, they are equipped with a diverse toolkit designed to navigate every stage of the creative journey. From data acquisition and preprocessing to model selection and training, each step is meticulously outlined with clear explanations and actionable strategies. Moreover, the handbook addresses common challenges and pitfalls, providing troubleshooting tips and best practices to optimize performance and enhance efficiency. Central to the handbook's approach is the emphasis on practical application. Through real-world examples and case studies, readers gain valuable insights into how RAG technology can be leveraged across various domains, from literature and journalism to gaming and virtual reality. Furthermore, the handbook explores ethical considerations and implications, prompting readers to critically evaluate the societal impact of AI-driven content creation. In addition to technical guidance, the handbook underscores the importance of creativity and human involvement in the storytelling process. It encourages readers to experiment, iterate, and collaborate, fostering a dynamic environment conducive to innovation and artistic expression. Ultimately, "From Concept to Creation: Retrieval-Augmented Generation (RAG) Handbook" serves as a roadmap for aspiring storytellers, researchers, and AI enthusiasts alike. By demystifying RAG technology and empowering readers with the knowledge and skills to wield it effectively, this handbook paves the way for a new era of narrative exploration and innovation.
Author: Maria Teresa Pazienza
Publisher: Springer
ISBN: 3540450920
Category : Computers
Languages : en
Pages : 166
Get Book Here
Book Description
The revised versions of lectures given at the Summer Convention on Information Extraction, SCIE 2002, held in Frascati, Italy in July 2002. The following lectures by leading authorities in the field of information extraction are included: - acquisition of domain knowledge - terminology mining - finite-state approaches to Web IE - measuring term representatives - agent-based ontological mediation in IE systems - information retrieval and IE in question answering systems - natural language communication with virtual actors
Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912
Get Book Here
Book Description
Author: Zhiyuan Liu
Publisher: Springer Nature
ISBN: 9811555737
Category : Computers
Languages : en
Pages : 319
Get Book Here
Book Description
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
Author: Etienne Noumen
Publisher: Etienne Noumen
ISBN:
Category : Computers
Languages : en
Pages : 147
Get Book Here
Book Description
Dive into the revolutionary world of Artificial Intelligence with 'AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence'. This comprehensive guide is your portal to understanding AI's most intricate concepts and cutting-edge developments. Whether you're a curious beginner or an AI enthusiast, this book is tailored to unveil the complexities of AI in a simple, accessible manner. What's Inside: Fundamental AI Concepts: Journey through the basics of AI, machine learning, deep learning, and neural networks. AI in Action: Explore how AI is reshaping industries and society, diving into its applications in computer vision, natural language processing, and beyond. Ethical AI: Tackle critical issues like AI ethics and bias, understanding the moral implications of AI advancements. Industry Insights: Gain insights into how AI is revolutionizing industries and impacting our daily lives. The Future of AI: Forecast the exciting possibilities and challenges that lie ahead in the AI landscape. Special Focus on Generative AI & LLMs: Latest AI Trends: Stay updated with the latest in AI, including ChatGPT, Google Bard, GPT-4, Gemini, and more. Interactive Quizzes: Test your knowledge with engaging quizzes on Generative AI and Large Language Models (LLMs). Practical Guides: Master GPT-4 with a simplified guide, delve into advanced prompt engineering, and explore the nuances of temperature settings in AI. Real-World Applications: Learn how to leverage AI in various sectors, from healthcare to cybersecurity, and even explore its potential in areas like aging research and brain implants. For the AI Enthusiast: Prompt Engineering: Uncover secrets to crafting effective prompts for ChatGPT/Google Bard. AI Career Insights: Explore lucrative career paths in AI, including roles like AI Prompt Engineers. AI Investment Guide: Navigate the world of AI stocks and investment opportunities. Your Guide to Navigating AI: Do-It-Yourself Tutorials: From building custom ChatGPT applications to running LLMs locally, this book offers step-by-step guides. AI for Everyday Use: Learn how AI can assist in weight loss, social media, and more. 'AI Unraveled' is more than just a book; it's a resource for anyone looking to grasp the complexities of AI and its impact on our world. Get ready to embark on an enlightening journey into the realm of Artificial Intelligence!" More Topics Covered: Artificial Intelligence, Machine Learning, Deep Learning, NLP, AI Ethics, Robotics, Cognitive Computing, ChatGPT, OpenAI, Google Bard, Generative AI, LLMs, AI in Healthcare, AI Investments, and much more. GPT-4 vs Gemini: Pros and Cons Mastering GPT-4: Simplified Guide For everyday Users Advance Prompt Engineering Techniques: [Single Prompt Technique, Zero-Shot and Few-Shot, Zero-Shot and Few-Shot, Generated Knowledge Prompting, EmotionPrompt, Chain of Density (CoD), Chain of Thought (CoT), Validation of LLMs Responses, Chain of Verification (CoVe), Agents - The Frontier of Prompt Engineering, Prompt Chaining vs Agents, Tree of Thought (ToT), ReAct (Reasoning + Act), ReWOO (Reasoning WithOut Observation), Reflexion and Self-Reflection, Guardrails, RAIL (Reliable AI Markup Language), Guardrails AI, NeMo Guardrails] Understanding Temperature in GPT-4: A Guide to AI Probability and Creativity Retrieval-Augmented Generation (RAG) model in the context of Large Language Models (LLMs) like GPT-4 Prompt Ideas for ChatGPT/Google Bard How to Run ChatGPT-like LLMs Locally on Your Computer in 3 Easy Steps ChatGPT Custom Instructions Settings for Power Users Examples of bad and good ChatGPT prompts Top 5 Beginner Mistakes in Prompt Engineering Use ChatGPT like a PRO Prompt template for learning any skill Prompt Engineering for ChatGPT The Future of LLMs in Search What is Explainable AI? Which industries are meant for XAI? ChatGPT Best Tips, Cheat Sheet LLMs Utilize Vector DB for Data Storage The Limitation Technique in Prompt Responses Use ChatGPT to learn new subjects Prompts to proofread anything Topics: Artificial Intelligence Education Machine Learning Deep Learning Reinforcement Learning Neural networks Data science AI ethics Deepmind Robotics Natural language processing Intelligent agents Cognitive computing AI Apps AI impact AI Tech ChatGPT Open AI Safe AI Generative AI Discriminative AI Sam Altman Google Bard NVDIA Large Language Models (LLMs) PALM GPT Explainable AI GPUs AI Stocks AI Podcast Q* AI Certification AI Quiz RAG How to access the AI Unraveled print and audiobook: Amazon print book: https://amzn.to/3xvCfWR Audible at Amazon : https://www.audible.com/pd/B0BXMJ7FK5/?source_code=AUDFPWS0223189MWT-BK-ACX0-343437&ref=acx_bty_BK_ACX0_343437_rh_us (Use Promo code: 37YT3B5UYUYZW) Audiobook at Google: https://play.google.com/store/audiobooks/details?id=AQAAAEAihFTEZM Amazon eBook: https://amzn.to/3KbshkO Google eBook: https://play.google.com/store/books/details?id=oySuEAAAQBAJ Apple eBook: http://books.apple.com/us/book/id6445730691
Author: Nicky Huys
Publisher: Nicky Huys Books
ISBN:
Category : Computers
Languages : en
Pages : 119
Get Book Here
Book Description
"The Digital Mind: Exploring Artificial Intelligence" delves into the profound implications of AI on the human experience. From the evolution of machine learning to its impact on cognitive processes, this book navigates the intricate intersection of technology and the human mind. Through captivating insights and compelling narratives, it examines the ethical, social, and philosophical dimensions of AI, offering a thought-provoking exploration of the digital landscape's transformative potential. Delving into the depths of neural networks and the future of human-machine interaction, "The Digital Mind" illuminates the dynamic convergence of artificial and organic intelligence, shaping a compelling vision of tomorrow's digital world.
