Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Deep Learning for Natural Language Processing
Humans do a great job of reading text, identifying key ideas, summarizing, making connections, and other tasks that require comprehension and context. Recent advances in deep learning make it possible for computer systems to achieve similar results. Deep Learning for Natural Language Processing teaches you to apply deep learning methods to natural language processing (NLP) to interpret and use text effectively. In this insightful book, (NLP) expert Stephan Raaijmakers distills his extensive knowledge of the latest state-of-the-art developments in this rapidly emerging field. Key features An overview of NLP and deep learning - Models for textual similarity - Deep memory-based NLP - Semantic r...
Recent Advances in Parsing Technology
In Marcus (1980), deterministic parsers were introduced. These are parsers which satisfy the conditions of Marcus's determinism hypothesis, i.e., they are strongly deterministic in the sense that they do not simulate non determinism in any way. In later work (Marcus et al. 1983) these parsers were modified to construct descriptions of trees rather than the trees them selves. The resulting D-theory parsers, by working with these descriptions, are capable of capturing a certain amount of ambiguity in the structures they build. In this context, it is not clear what it means for a parser to meet the conditions of the determinism hypothesis. The object of this work is to clarify this and other issues pertaining to D-theory parsers and to provide a framework within which these issues can be examined formally. Thus we have a very narrow scope. We make no ar guments about the linguistic issues D-theory parsers are meant to address, their relation to other parsing formalisms or the notion of determinism in general. Rather we focus on issues internal to D-theory parsers themselves.
Large Language Models
An in-depth history of Large Language Models—and what their ubiquity, disruption, and creativity mean from a wider sociopolitical perspective. In November 2022, ChatGPT swept the globe with a mixed frenzy of excitement and anxiety. Was this a step closer to reaching singularity or just another marvel in machine learning? Author Stephan Raaijmakers provides a comprehensive introduction to Large Language Models (LLMs), describing what exactly they are capable of from a technical and creative standpoint. This concise volume covers everything from the architecture of LLM neural networks to the limitations of LLMs to how our governments can regulate this technology. In explaining how exactly LLMs learn from data sets, Raaijmakers defangs the more sensational arguments we may be familiar with. Instead, he offers a more grounded approach to how this groundbreaking—and increasingly ubiquitous—form of artificial intelligence will shape our society for years to come.
Trustworthy AI - Integrating Learning, Optimization and Reasoning
This book constitutes the thoroughly refereed conference proceedings of the First International Workshop on the Foundation of Trustworthy AI - Integrating Learning, Optimization and Reasoning, TAILOR 2020, held virtually in September 2020, associated with ECAI 2020, the 24th European Conference on Artificial Intelligence. The 11 revised full papers presented together with 6 short papers and 6 position papers were reviewed and selected from 52 submissions. The contributions address various issues for Trustworthiness, Learning, reasoning, and optimization, Deciding and Learning How to Act, AutoAI, and Reasoning and Learning in Social Contexts.
Machine Learning for Multimodal Interaction
This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2008, held in Utrecht, The Netherlands, in September 2008. The 12 revised full papers and 15 revised poster papers presented together with 5 papers of a special session on user requirements and evaluation of multimodal meeting browsers/assistants were carefully reviewed and selected from 47 submissions. The papers cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction, using several communication modalities. Special focus is given to the analysis of non-verbal communication cues and social signal processing, the analysis of communicative content, audio-visual scene analysis, speech processing, interactive systems and applications.
Deep Learning with Structured Data
Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Summary Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub ...
Memory-Based Language Processing
Memory-based language processing--a machine learning and problem solving method for language technology--is based on the idea that the direct re-use of examples using analogical reasoning is more suited for solving language processing problems than the application of rules extracted from those examples. This book discusses the theory and practice of memory-based language processing, showing its comparative strengths over alternative methods of language modelling. Language is complex, with few generalizations, many sub-regularities and exceptions, and the advantage of memory-based language processing is that it does not abstract away from this valuable low-frequency information.
ICT Critical Infrastructures and Society
This book constitutes the refereed proceedings of the 10th IFIP TC 9 International Conference on Human Choice and Computers, HCC10 2012, held in Amsterdam, The Netherlands, in September 2012. The 37 revised full papers presented were carefully reviewed and selected for inclusion in the volume. The papers are organized in topical sections on national and international policies, sustainable and responsible innovation, ICT for peace and war, and citizens' involvement, citizens' rights and ICT.
Multilingual Information Access Evaluation II - Multimedia Experiments
This book constitutes the thoroughly refereed proceedings of the 10th Workshop of the Cross Language Evaluation Forum, CLEF 2010, held in Corfu, Greece, in September/October 2009. The volume reports experiments on various types of multimedia collections. It is divided into three main sections presenting the results of the following tracks: Interactive Cross-Language Retrieval (iCLEF), Cross-Language Image Retrieval (ImageCLEF), and Cross-Language Video Retrieval (VideoCLEF).
Automated Technology for Verification and Analysis
This book constitutes the refereed proceedings of the 18th International Symposium on Automated Technology for Verification and Analysis, ATVA 2020, held in Hanoi, Vietnam, in October 2020. The 27 regular papers presented together with 5 tool papers and 2 invited papers were carefully reviewed and selected from 75 submissions. The symposium is dedicated to promoting research in theoretical and practical aspects of automated analysis, verification and synthesis by providing an international venue for the researchers to present new results. The papers focus on neural networks and machine learning; automata; logics; techniques for verification, analysis and testing; model checking and decision procedures; synthesis; and randomization and probabilistic systems.
