Domain oxed.de kaufen?

Produkt zum Begriff Natural Language Processing:


  • Real-World Natural Language Processing
    Real-World Natural Language Processing

    Voice assistants, automated customer service agents, and other cutting-edge human-to-computer interactions rely on accurately interpreting language as it is written and spoken. Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you’ll explore the core tools and techniques required to build a huge range of powerful NLP apps.about the technologyNatural language processing is the part of AI dedicated to understanding and generating human text and speech. NLP covers a wide range of algorithms and tasks, from classic functions such as spell checkers, machine translation, and search engines to emerging innovations like chatbots, voice assistants, and automatic text summarization. Wherever there is text, NLP can be useful for extracting meaning and bridging the gap between humans and machines.about the bookReal-world Natural Language Processing teaches you how to create practical NLP applications using Python and open source NLP libraries such as AllenNLP and Fairseq. In this practical guide, you’ll begin by creating a complete sentiment analyzer, then dive deep into each component to unlock the building blocks you’ll use in all different kinds of NLP programs. By the time you’re done, you’ll have the skills to create named entity taggers, machine translation systems, spelling correctors, and language generation systems. what's insideDesign, develop, and deploy basic NLP applicationsNLP libraries such as AllenNLP and FairseqAdvanced NLP concepts such as attention and transfer learningabout the readerAimed at intermediate Python programmers. No mathematical or machine learning knowledge required.about the authorMasato Hagiwara received his computer science PhD from Nagoya University in 2009, focusing on Natural Language Processing and machine learning. He has interned at Google and Microsoft Research, and worked at Baidu Japan, Duolingo, and Rakuten Institute of Technology. He now runs his own consultancy business advising clients, including startups and research institutions.

    Preis: 58.84 € | Versand*: 0 €
  • Multilingual Natural Language Processing Applications: From Theory to Practice
    Multilingual Natural Language Processing Applications: From Theory to Practice

    Multilingual Natural Language Processing Applications is the first comprehensive single-source guide to building robust and accurate multilingual NLP systems. Edited by two leading experts, it integrates cutting-edge advances with practical solutions drawn from extensive field experience.   Part I introduces the core concepts and theoretical foundations of modern multilingual natural language processing, presenting today’s best practices for understanding word and document structure, analyzing syntax, modeling language, recognizing entailment, and detecting redundancy.   Part II thoroughly addresses the practical considerations associated with building real-world applications, including information extraction, machine translation, information retrieval/search, summarization, question answering, distillation, processing pipelines, and more.   This book contains important new contributions from leading researchers at IBM, Google, Microsoft, Thomson Reuters, BBN, CMU, University of Edinburgh, University of Washington, University of North Texas, and others.   Coverage includes Core NLP problems, and today’s best algorithms for attacking them Processing the diverse morphologies present in the world’s languagesUncovering syntactical structure, parsing semantics, using semantic role labeling, and scoring grammaticalityRecognizing inferences, subjectivity, and opinion polarityManaging key algorithmic and design tradeoffs in real-world applications Extracting information via mention detection, coreference resolution, and eventsBuilding large-scale systems for machine translation, information retrieval, and summarizationAnswering complex questions through distillation and other advanced techniquesCreating dialog systems that leverage advances in speech recognition, synthesis, and dialog managementConstructing common infrastructure for multiple multilingual text processing applications   This book will be invaluable for all engineers, software developers, researchers, and graduate students who want to process large quantities of text in multiple languages, in any environment: government, corporate, or academic.

    Preis: 49.21 € | Versand*: 0 €
  • Transfer Learning for Natural Processing
    Transfer Learning for Natural Processing

    Building and training deep learning models from scratch is costly, time-consuming, and requires massive amounts of data. To address this concern, cutting-edge transfer learning techniques enable you to start with pretrained models you can tweak to meet your exact needs. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre takes you hands-on with customizing these open source resources for your own NLP architectures. You’ll learn how to use transfer learning to deliver state-of-the-art results even when working with limited label data, all while saving on training time and computational costs.about the technologyTransfer learning enables machine learning models to be initialized with existing prior knowledge. Initially pioneered in computer vision, transfer learning techniques have been revolutionising Natural Language Processing with big reductions in the training time and computation power needed for a model to start delivering results. Emerging pretrained language models such as ELMo and BERT have opened up new possibilities for NLP developers working in machine translation, semantic analysis, business analytics, and natural language generation.about the bookTransfer Learning for Natural Language Processing is a practical primer to transfer learning techniques capable of delivering huge improvements to your NLP models. Written by DARPA researcher Paul Azunre, this practical book gets you up to speed with the relevant ML concepts before diving into the cutting-edge advances that are defining the future of NLP. You’ll learn how to adapt existing state-of-the art models into real-world applications, including building a spam email classifier, a movie review sentiment analyzer, an automated fact checker, a question-answering system and a translation system for low-resource languages. what's insideFine tuning pretrained models with new domain dataPicking the right model to reduce resource usageTransfer learning for neural network architecturesFoundations for exploring NLP academic literatureabout the readerFor machine learning engineers and data scientists with some experience in NLP.about the authorPaul Azunre holds a PhD in Computer Science from MIT and has served as a Principal Investigator on several DARPA research programs. He founded Algorine Inc., a Research Lab dedicated to advancing AI/ML and identifying scenarios where they can have a significant social impact. Paul also co-founded Ghana NLP, an open source initiative focused using NLP and Transfer Learning with Ghanaian and other low-resource languages. He frequently contributes to major peer-reviewed international research journals and serves as a program committee member at top conferences in the field.

    Preis: 49.21 € | Versand*: 0 €
  • Learning Deep Learning: Theory and Practice of Neural Networks, Computer Vision, Natural Language Processing, and Transformers Using TensorFlow
    Learning Deep Learning: Theory and Practice of Neural Networks, Computer Vision, Natural Language Processing, and Transformers Using TensorFlow

    NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results"To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals."--From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA"Ekman uses a learning technique that in our experience has proven pivotal to successasking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us."--From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning InstituteDeep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience.After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images.Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning.Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagationSee how DL frameworks make it easier to develop more complicated and useful neural networksDiscover how convolutional neural networks (CNNs) revolutionize image classification and analysisApply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequencesMaster NLP with sequence-to-sequence networks and the Transformer architectureBuild applications for natural language translation and image captioningNVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others.Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

    Preis: 43.86 € | Versand*: 0 €
  • Wie können Natural Language Processing-Technologien Unternehmen dabei unterstützen, ihre Kundenkommunikation zu verbessern? Welche Anwendungen hat Natural Language Processing in der medizinischen Diagnose und Behandlung?

    Natural Language Processing-Technologien können Unternehmen dabei unterstützen, ihre Kundenkommunikation zu verbessern, indem sie automatisierte Chatbots einsetzen, um Kundenanfragen schnell und effizient zu beantworten. Zudem können sie Feedback-Analysen durchführen, um Kundenbedürfnisse besser zu verstehen und ihre Produkte oder Dienstleistungen entsprechend anzupassen. In der medizinischen Diagnose und Behandlung kann Natural Language Processing eingesetzt werden, um Patientenakten zu analysieren und wichtige Informationen für Ärzte zu extrahieren. Zudem können NLP-Technologien bei der automatisierten Auswertung von medizinischen Studien und Forschungsergebnissen helfen, um neue Erkenntnisse zu gewinnen und die Behandlungsmethoden zu

  • Was sind die Anwendungsmöglichkeiten von Natural Language Processing in der heutigen Technologie?

    Natural Language Processing wird in der Spracherkennung für virtuelle Assistenten wie Siri oder Alexa verwendet. Es ermöglicht die automatische Übersetzung von Texten in verschiedene Sprachen. Zudem wird NLP in der Sentimentanalyse eingesetzt, um die Stimmung und Meinungen in sozialen Medien oder Kundenbewertungen zu analysieren.

  • Was sind die grundlegenden Prinzipien und Anwendungen von Natural Language Processing (NLP)?

    Die grundlegenden Prinzipien von Natural Language Processing beinhalten die Verarbeitung und Analyse von natürlicher Sprache durch Computer. Anwendungen von NLP umfassen Textübersetzung, Chatbots, Sentimentanalyse und Spracherkennung. NLP wird in verschiedenen Bereichen wie der Medizin, der Finanzbranche und der Kundenbetreuung eingesetzt.

  • Was sind die wichtigsten Anwendungen von Natural Language Processing in der heutigen Technologie?

    Die wichtigsten Anwendungen von Natural Language Processing in der heutigen Technologie sind Chatbots, Spracherkennung und Sentimentanalyse. Chatbots ermöglichen die Interaktion mit Kunden auf natürliche Weise, Spracherkennung ermöglicht die Steuerung von Geräten durch Sprachbefehle und Sentimentanalyse hilft Unternehmen, das Feedback ihrer Kunden besser zu verstehen.

Ähnliche Suchbegriffe für Natural Language Processing:


  • Digital Signal Processing
    Digital Signal Processing

    A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.

    Preis: 53.49 € | Versand*: 0 €
  • Digital Video Processing
    Digital Video Processing

    Over the years, thousands of engineering students and professionals relied on Digital Video Processing as the definitive, in-depth guide to digital image and video processing technology. Now, Dr. A. Murat Tekalp has completely revamped the first edition to reflect today’s technologies, techniques, algorithms, and trends.   Digital Video Processing, Second Edition, reflects important advances in image processing, computer vision, and video compression, including new applications such as digital cinema, ultra-high-resolution video, and 3D video.   This edition offers rigorous, comprehensive, balanced, and quantitative coverage of image filtering, motion estimation, tracking, segmentation, video filtering, and compression. Now organized and presented as a true tutorial, it contains updated problem sets and new MATLAB projects in every chapter.   Coverage includes Multi-dimensional signals/systems: transforms, sampling, and lattice conversion Digital images and video: human vision, analog/digital video, and video quality Image filtering: gradient estimation, edge detection, scaling, multi-resolution representations, enhancement, de-noising, and restoration Motion estimation: image formation; motion models; differential, matching, optimization, and transform-domain methods; and 3D motion and shape estimation Video segmentation: color and motion segmentation, change detection, shot boundary detection, video matting, video tracking, and performance evaluation Multi-frame filtering: motion-compensated filtering, multi-frame standards conversion, multi-frame noise filtering, restoration, and super-resolution Image compression: lossless compression, JPEG, wavelets, and JPEG2000 Video compression: early standards, ITU-T H.264/MPEG-4 AVC, HEVC, Scalable Video Compression, and stereo/multi-view approaches

    Preis: 97.36 € | Versand*: 0 €
  • Body Language
    Body Language

    Never mind what you think you’re saying, what is your body saying? Over half of our communication is through our bodies, but how many of us know how to decipher this non-verbal language? Body Language will make sure you get it right every time. In seven simple lessons you’ll become an expert at reading others and controlling your own gestures to get the response you want. This definitive and indispensable guide to body language will help you: Make a good impression and be instantly likeable Match what you’re saying to the signals you’re sending so you send out clear, credible messages Learn how to read other people’s faces, eyes and tone of voice effectively Decipher the language of the limbs, from folded arms to crossed legs Figure out quickly when someone is lying James Borg’s Body Language will give you the magic formula to mastering the power of body language – the ultimate way to achieve success in work and life. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.

    Preis: 9.62 € | Versand*: 0 €
  • Discrete-Time Signal Processing
    Discrete-Time Signal Processing

    For senior/graduate-level courses in Discrete-Time Signal Processing.THE definitive, authoritative text on DSP — ideal for those with an introductory-level knowledge of signals and systems. Written by prominent DSP pioneers, it provides thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete-time Fourier Analysis. By focusing on the general and universal concepts in discrete-time signal processing, it remains vital and relevant to the new challenges arising in the field.

    Preis: 101.01 € | Versand*: 0 €
  • Was sind Wortvektoren und wie werden sie in der Natural Language Processing eingesetzt?

    Wortvektoren sind numerische Darstellungen von Wörtern, die ihre Bedeutung und Beziehung zu anderen Wörtern im Text erfassen. Sie werden in Natural Language Processing verwendet, um Wörter in einem Text in einen mathematischen Raum zu projizieren, um semantische Ähnlichkeiten und Beziehungen zwischen Wörtern zu erfassen. Diese Vektoren werden häufig für Aufgaben wie Wortähnlichkeitsberechnung, Textklassifizierung und maschinelles Übersetzen eingesetzt.

  • Wie beeinflusst Natural Language Processing die Entwicklung von Chatbots in der Kundenbetreuung, medizinischen Diagnose und anderen Anwendungen?

    Natural Language Processing (NLP) ermöglicht es Chatbots, natürliche Sprache zu verstehen und darauf zu reagieren, was die Interaktion mit Kunden in der Kundenbetreuung verbessert. In der medizinischen Diagnose kann NLP dazu beitragen, große Mengen an Patientendaten zu analysieren und relevante Informationen zu extrahieren, um Ärzten bei der Diagnose und Behandlung zu unterstützen. In anderen Anwendungen ermöglicht NLP eine präzisere Analyse von Textdaten, was zu einer verbesserten Automatisierung und Effizienz führt. Darüber hinaus kann NLP dazu beitragen, Sprachbarrieren zu überwinden und die Kommunikation in verschiedenen Sprachen zu erleichtern.

  • Was sind die grundlegenden Prinzipien des Natural Language Processing und wie beeinflussen sie die Entwicklung von Sprachtechnologie?

    Die grundlegenden Prinzipien des Natural Language Processing sind die Verarbeitung von natürlicher Sprache durch Computer, die Analyse von Texten und die Umwandlung von Sprache in strukturierte Daten. Diese Prinzipien beeinflussen die Entwicklung von Sprachtechnologie, indem sie es ermöglichen, maschinelle Übersetzungen, Chatbots, Spracherkennungssysteme und andere Anwendungen zu entwickeln, die die Kommunikation zwischen Mensch und Maschine verbessern. Durch die Anwendung von NLP-Prinzipien können Computer menschenähnliche Fähigkeiten im Umgang mit Sprache erlangen und komplexe Aufgaben im Bereich der Sprachverarbeitung ausführen.

  • Wie beeinflusst Natural Language Processing die Entwicklung von automatisierten Sprachverarbeitungssystemen? In welchen Bereichen kann NLP zukünftig eingesetzt werden?

    Natural Language Processing (NLP) ermöglicht es automatisierten Sprachverarbeitungssystemen, menschliche Sprache zu verstehen, zu verarbeiten und darauf zu reagieren. Durch NLP können Systeme wie Chatbots, Übersetzungssoftware und Spracherkennungstechnologien verbessert werden. Zukünftig kann NLP in Bereichen wie Kundenservice, Gesundheitswesen, Bildung und Finanzwesen eingesetzt werden, um die Interaktion zwischen Mensch und Maschine zu erleichtern.

* Alle Preise verstehen sich inklusive der gesetzlichen Mehrwertsteuer und ggf. zuzüglich Versandkosten. Die Angebotsinformationen basieren auf den Angaben des jeweiligen Shops und werden über automatisierte Prozesse aktualisiert. Eine Aktualisierung in Echtzeit findet nicht statt, so dass es im Einzelfall zu Abweichungen kommen kann.