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  • 1
    Online Resource
    Online Resource
    O'Reilly book club : audio collection 2023 (2023)
    [Place of publication not identified] : O'Reilly Media, Inc.
    Details
    Language: English
    Pages: 1 online resource (1 audio file (1 hr., 49 min.))
    Edition: [First edition].
    DDC: 808.02
    Keywords: Authorship ; Audiobooks
    Abstract: Look no further for the 2023 audio-only collection of O'Reilly Book Club interviews. Hear directly from our authors about their book writing processes and gain insight into how they've become the subject matter experts in their fields.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 7, 2023)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Praxiseinstieg Machine Learning mit Scikit-Learn, Keras und TensorFlow : Konzepte, Tools und Techniken für intelligente Systeme (2023)
    Heidelberg : dpunkt
    Details
    Language: German
    Pages: 1 online resource (878 pages) , illustrations
    Edition: 3., aktualisierte und erweiterte Auflage.
    Uniform Title: Hands-on machine learning with Scikit-Learn and TensorFlow
    DDC: 006.3/1
    Keywords: Machine learning ; Artificial intelligence
    Abstract: Eine Reihe technischer Durchbrüche beim Deep Learning haben das gesamte Gebiet des maschinellen Lernens in den letzten Jahren beflügelt. Inzwischen können sogar Programmierer, die kaum etwas über diese Technologie wissen, mit einfachen, effizienten Werkzeugen Machine-Learning-Programme implementieren. Dieses praxisorientierte Buch zeigt Ihnen wie. Mit konkreten Beispielen, einem Minimum an Theorie und zwei unmittelbar anwendbaren Python-Frameworks - Scikit-Learn und TensorFlow 2 - verhilft Ihnen der Autor Aurélien Géron zu einem intuitiven Verständnis der Konzepte und Tools für das Entwickeln intelligenter Systeme. Sie lernen eine Vielzahl von Techniken kennen, beginnend mit einfacher linearer Regression bis hin zu Deep Neural Networks. Die in jedem Kapitel enthaltenen Übungen helfen Ihnen, das Gelernte in die Praxis umzusetzen. Um direkt zu starten, benötigen Sie lediglich etwas Programmiererfahrung.
    Note: Includes index
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Natural language processing using transformer architectures (2020)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 45 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Whether you need to automatically judge the sentiment of a user review, summarize long documents, translate text, or build a chatbot, you need the best language model available. In 2018, pretty much every NLP benchmark was crushed by novel transformer-based architectures, replacing long-standing architectures based on recurrent neural networks. In short, if you’re into NLP, you need transformers. But to use transformers, you need to know what they are, what transformer-based architectures look like, and how you can implement them in your projects. Aurélien Géron (Kiwisoft) dives into recurrent neural networks and their limits, the invention of the transformer, attention mechanisms, the transformer architecture, subword tokenization using SentencePiece, self-supervised pretraining—learning from huge corpora, one-size-fits-all language models, BERT and GPT 2, and how to use these language models in your projects using TensorFlow. What you'll learn Understand transformers and modern language models and how they can tackle complex NLP tasks Identify what tools to use and what the code looks like
    Note: Online resource; Title from title screen (viewed February 28, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    Neural networks and deep learning (2018)
    [Place of publication not identified] : O'Reilly
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Neural networks are at the very core of deep learning. They are versatile, powerful, and scalable, making them ideal to tackle large and highly complex Machine Learning tasks, such as classifying billions of images (e.g., Google Images), powering speech recognition services (e.g., Apple's Siri), recommending the best videos to watch to hundreds of millions of users every day (e.g., YouTube), or learning to beat the world champion at the game of Go by examining millions of past games and then playing against itself (DeepMind's AlphaGo). This lesson introduces artificial neural networks, starting with a quick tour of the very first ANN architectures, then covering topics such as training neural nets, recurrent neural networks, and reinforcement learning. This lesson will clarify what neural networks are and why you may want to use them.
    Note: "From Hands-on machine learning with Scikit-Learn and TensorFlow by Aurélien Géron"--Cover. - Date of publication from resource description page. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 16, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781492037354/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    Getting started with TensorFlow (2017)
    [Place of publication not identified] : O'Reilly
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: This Lesson will answer your key questions about getting started with TensorFlow, a library for machine learning and working with deep neural networks. What you'll learn-and how you can apply it You'll learn the necessary basics to get starting using TensorFlow and will be able to follow TensorFlow tutorials. This lesson is for you because You've gained a technical understanding of TensorFlow basics and are ready to move to the next step of training a very large neural network. You want to learn the basics of TensorFlow, including installation, managing graphs, placeholders, and optimization. You have some programming experience and you eventually want to take your skills to the next level and train very large neural nets. You don't have much experience in deep learning libraries, hands-on with examples of code. Prerequisites: Understanding of gradient descent Programming experience (understanding of how to code in Python) Materials or downloads needed: Python TensorFlow (recommend latest version, code written and tested on v. 0.11)
    Note: "From Hands-on machine learning with Scikit-Learn and TensorFlow by Aurélien Géron"--Cover. - Date of publication from resource description page. - Description based on online resource; title from title page (Safari, viewed May 25, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781491978757/?ar
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Understanding support vector machines (2017)
    [Place of publication not identified] : O'Reilly
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: What you'll learn-and how you can apply it You'll learn the core concepts one of the most popular models in Machine Learning-support vector machines-how to use them, and how they work. Readers will gain an intuitive understanding of the mathematics involved in SVMs, including an introduction to using polynomial kernels. At the end of this Lesson, readers will be able to do binary classification for rather simple problems. This lesson is for you because You have some programming experience and you're ready to code a Machine Learning project. You want to classify attributes on small- to medium-sized datasets and possibly complex datasets. Prerequisites: Have some programming experience (know how to code in Python) Understanding of basic machine learning concepts (fitting a model to data) Materials or downloads needed: Python Scikit-Learn (code written and tested on v. 0.18)
    Note: "From Hands-on machine learning with Scikit-Learn and TensorFlow by Aurélien Géron"--Cover. - Date of publication from resource description page. - Description based on online resource; title from title page (Safari, viewed May 25, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781491978733/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 7
    Online Resource
    Online Resource
    Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Graphics in this book are printed in black and white . Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks-scikit-learn and TensorFlow-author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets Apply practical code examples without acquiring excessive machine learning theory or algorithm details
    Note: Includes index. - Description based on online resource; title from title page (Safari, viewed March 22, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781491962282/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 8
    Online Resource
    Online Resource
    Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (848 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
    Note: Online resource; Title from title page (viewed September 30, 2019)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 9
    Online Resource
    Online Resource
    Natural Language Processing mit Transformern : Sprachanwendungen mit Hugging Face erstellen (2023)
    Heidelberg : dpunkt
    Details
    Language: German
    Pages: 1 online resource (432 pages) , illustrations
    Edition: 1. Auflage.
    Uniform Title: Natural language processing with transformers
    DDC: 006.3/5
    Keywords: Natural language processing (Computer science) ; Python (Computer program language) ; Machine learning ; Cloud computing
    Abstract: Transformer haben sich seit ihrer Einführung nahezu über Nacht zur vorherrschenden Architektur im Natural Language Processing entwickelt. Sie liefern die besten Ergebnisse für eine Vielzahl von Aufgaben bei der maschinellen Sprachverarbeitung. Wenn Sie Data Scientist oder Programmierer sind, zeigt Ihnen dieses praktische Buch, wie Sie NLP-Modelle mit Hugging Face Transformers, einer Python-basierten Deep-Learning-Bibliothek, trainieren und skalieren können. Transformer kommen beispielsweise beim maschinellen Schreiben von Nachrichtenartikeln zum Einsatz, bei der Verbesserung von Google-Suchanfragen oder bei Chatbots. In diesem Handbuch zeigen Ihnen Lewis Tunstall, Leandro von Werra und Thomas Wolf, die auch die Transformers-Bibliothek von Hugging Face mitentwickelt haben, anhand eines praktischen Ansatzes, wie Transformer-basierte Modelle funktionieren und wie Sie sie in Ihre Anwendungen integrieren können. Sie werden schnell eine Vielzahl von Aufgaben wie Textklassifikation, Named Entity Recognition oder Question Answering kennenlernen, die Sie mit ihnen lösen können.
    Note: Includes bibliographical references and index
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 10
    Online Resource
    Online Resource
    O'Reilly Book Club : Aurélien Géron on hands-on machine learning with Scikit-Learn, Keras, and TensorFlow (2023)
    [Place of publication not identified] : O'Reilly Media, Inc.
    Details
    Language: English
    Pages: 1 online resource (1 video file (59 min.)) , sound, color.
    Edition: Third edition.
    DDC: 006.3/1
    Keywords: Machine learning ; Machine learning ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Join us for this edition of O'Reilly Book Club with Aurélien Géron, author of Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, to learn about the fundamentals of machine learning. You'll cover everything from working with real data to training and deploying models as you learn tricks of the trade, listen to stories, ask your questions, and connect with other readers. What you'll learn and how you can apply it Learn the concepts, tools, and techniques for doing end-to-end machine learning Explore the latest deep learning technologies, such as vision transformers, multimodal models, and more Find out how to update your machine learning systems for state-of-the-art performance This recording of a live event is for you because... You want to go beyond the words on the page and hear from the expert. You're a machine learning practitioner who wants to learn about the latest developments in the field, including updates to scikit-learn and Keras, large language models, and new generative learning tools such as diffusion models. Recommended follow-up: Read Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, third edition (book) Watch Natural Language Processing Using Transformer Architectures (video) Read TensorFlow 2 Pocket Reference (book).
    Note: Online resource; title from title details screen (O'Reilly, viewed June 26, 2023)
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
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