Produkte zum Begriff Natural Language Processing:
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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 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 € -
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: 66.33 € | Versand*: 0 € -
U&P AI - Natural Language Processing (NLP) with Python Alpha Academy Code
The U&P AI - Natural Language Processing (NLP) with Python course is a comprehensive guide to mastering NLP techniques using Python programming. Key Features: Learn the fundamentals of Natural Language Processing (NLP) with Python Dive into advanced NLP techniques such as sentiment analysis and text classification Gain practical experience through hands-on coding exercises and projects Benefits: Empowers learners to analyse and derive insights from textual data Enhances programming skills wit...
Preis: 10.99 € | Versand*: 0.00 EUR €
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Wie kann man sich selbst Machine Learning, Künstliche Intelligenz und Natural Language Processing beibringen?
Um sich selbst Machine Learning, Künstliche Intelligenz und Natural Language Processing beizubringen, gibt es verschiedene Möglichkeiten. Man kann Online-Kurse und Tutorials nutzen, um die Grundlagen zu erlernen und praktische Erfahrungen zu sammeln. Es ist auch hilfreich, an Projekten zu arbeiten und mit vorhandenen Tools und Bibliotheken zu experimentieren. Zudem kann der Austausch mit anderen Fachleuten in Foren und Communitys dabei helfen, Fragen zu klären und neue Ideen zu entwickeln.
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Was bedeutet "Fitness natural"?
"Fitness natural" bedeutet, dass man seine Fitness und körperliche Gesundheit auf natürliche Weise verbessert, ohne die Verwendung von leistungssteigernden Substanzen oder anderen künstlichen Methoden. Es bezieht sich auf einen gesunden und ausgewogenen Lebensstil, der regelmäßige Bewegung, eine gesunde Ernährung und ausreichend Ruhe und Erholung umfasst.
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Was genau ist ein Language Consultant?
Ein Language Consultant ist eine Person, die Unternehmen oder Einzelpersonen bei der Verbesserung ihrer sprachlichen Fähigkeiten und Kommunikationsfähigkeiten unterstützt. Sie können bei der Entwicklung von Sprachstrategien, der Verbesserung der Schreib- und Sprechfähigkeiten, der Übersetzung von Texten und anderen sprachlichen Aufgaben helfen. Ein Language Consultant kann auch bei der interkulturellen Kommunikation und der Anpassung an verschiedene Sprach- und Kulturkontexte unterstützen.
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Wie kann man Processing lernen?
Um Processing zu lernen, gibt es verschiedene Möglichkeiten. Eine Möglichkeit ist es, Tutorials und Online-Kurse zu nutzen, die speziell für Anfänger entwickelt wurden. Es gibt auch Bücher und Videos, die Schritt für Schritt Anleitungen und Beispiele bieten. Eine weitere Möglichkeit ist es, an Workshops oder Kursen teilzunehmen, in denen man von erfahrenen Processing-Entwicklern lernen kann. Es ist auch hilfreich, mit anderen Entwicklern in der Community zu interagieren und von ihren Erfahrungen zu lernen.
Ähnliche Suchbegriffe für Natural Language Processing:
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U&P AI - Natural Language Processing (NLP) with Python Alpha Academy Code
Der Kurs „U&P AI – Natural Language Processing (NLP) mit Python" ist ein umfassender Leitfaden zur Erlernung von NLP-Techniken mithilfe der Python-Programmierung. Hauptmerkmale: Lernen Sie die Grundlagen der Verarbeitung natürlicher Sprache (NLP) mit Python Tauchen Sie ein in fortgeschrittene NLP-Techniken wie Stimmungsanalyse und Textklassifizierung Sammeln Sie praktische Erfahrungen durch praxisnahe Programmierübungen und Projekte Vorteile: Befähigt Lernende, Textdaten zu analysieren und da...
Preis: 10.99 € | Versand*: 0.00 EUR € -
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
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 € -
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 €
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Was ist die Processing-Programmiersprache?
Die Processing-Programmiersprache ist eine Open-Source-Sprache, die speziell für die kreative Programmierung und die Erstellung von interaktiven Grafiken, Animationen und visuellen Effekten entwickelt wurde. Sie basiert auf Java und bietet eine einfache Syntax und eine umfangreiche Bibliothek, um komplexe visuelle Projekte zu erstellen. Processing wird häufig von Künstlern, Designern und Pädagogen verwendet.
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Ist Tim Gabel wirklich natural?
Es gibt keine definitive Antwort auf diese Frage, da es schwierig ist, die Verwendung von leistungssteigernden Substanzen bei einer Person zu bestätigen oder zu widerlegen. Tim Gabel behauptet, natural zu sein, aber es gibt auch Spekulationen und Vermutungen über seine mögliche Verwendung von Steroiden. Letztendlich ist es wichtig, dass jeder seine eigenen Entscheidungen trifft und die Wahrheit kann nur von Tim Gabel selbst bekannt gegeben werden.
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Was sind Natural Killer Zellen?
Was sind Natural Killer Zellen? Natural Killer Zellen sind eine Art von weißen Blutzellen, die eine wichtige Rolle im angeborenen Immunsystem spielen. Sie sind in der Lage, abnormale Zellen wie virale infizierte Zellen oder Krebszellen zu erkennen und zu zerstören, ohne dass sie zuvor sensibilisiert werden müssen. Natural Killer Zellen können ihre Ziele auf verschiedene Weisen angreifen, zum Beispiel durch die Freisetzung von Zytokinen oder durch direkten Zellkontakt. Sie sind entscheidend für die Abwehr von Infektionen und die Überwachung der Zellgesundheit im Körper.
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Wie viel Muskelmasse Natural möglich?
Wie viel Muskelmasse natural möglich ist, hängt von verschiedenen Faktoren ab, wie Genetik, Trainingsintensität, Ernährung und Regeneration. Im Durchschnitt können Männer ohne die Verwendung von leistungssteigernden Substanzen etwa 2-3 kg Muskelmasse pro Monat aufbauen. Frauen bauen in der Regel etwas langsamer Muskelmasse auf. Es ist wichtig, realistische Erwartungen zu haben und geduldig zu sein, da der Muskelaufbau ein langfristiger Prozess ist. Konsistenz im Training und eine ausgewogene Ernährung sind entscheidend, um das maximale Potenzial an natürlicher Muskelmasse zu erreichen.
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