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  • 1
    Online Resource
    Online Resource
    Google Anthos in action : manage hybrid and multicloud Kubernetes clusters (2023)
    Shelter Island, NY : Manning Publications
    Details
    ISBN: 9781633439573 , 1633439577
    Language: English
    Pages: 1 online resource (725 pages) , illustrations
    Parallel Title: Erscheint auch als
    DDC: 004.67/82
    Keywords: Kubernetes ; Cloud computing
    Abstract: Learn multicloud deployment on Anthos directly from the Google development team! Anthos delivers a consistent management platform for deploying and operating Linux and Windows applications anywhere—multi-cloud, edge, on-prem, bare metal, or VMware. Google Anthos in Action demystifies Anthos with practical examples of Anthos at work and invaluable insights from the Google team that built it. You’ll learn how to use this modern, Kubernetes-based cloud platform to balance costs, automate security, and run your software literally anywhere. The book is full of Google-tested patterns that will boost efficiency across the development lifecycle. It’s an absolutely essential guide for anyone working with Anthos, or delivering software in a cloud-centric world.
    Note: Includes index. - Description based on print version record
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Deep Learning with TensorFlow 2 and Keras - Second Edition (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (646 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key Features Introduces and then uses TensorFlow 2 and Keras right from the start Teaches key machine and deep learning techniques Understand the fundamentals of deep learning and machine learning through clear explanations and extensive code samples Book Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learn Build machine learning and deep learning systems with TensorFlow 2 and the Keras API Use Regression analysis, the most popular approach to machine learning Understand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiers Use GANs (generative adversarial networks) to create new data that fits with existing patterns Discover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret another Apply deep learning to natural human language and interpret natural language texts to produce an appropriate response Train your models on the cloud and put TF to work in real environments Explore how Google tools can automate simple ML workflows without the need for complex modeling Who this book is for This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. Whether or not you have done machine learning before, this book gives you the theory and practice required to use Keras, TensorFlow 2, and AutoML to build machine learning systems.
    Note: Online resource; Title from title page (viewed December 27, 2019) , 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.
  • 3
    Online Resource
    Online Resource
    Transformers for natural language processing : build, train, and fine-tuning deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, and GPT-3 (2022)
    [Birmingham, United Kingdom] : Packt Publishing
    Details
    ISBN: 9781803247335
    Language: English
    Pages: 1 online resource (564 pages) , illustrations
    Edition: Second edition.
    Series Statement: Expert insight
    Parallel Title: Erscheint auch als Rothman, Denis Transformers for natural language processing
    DDC: 006.3
    RVK:
    ST 306
    Keywords: Artificial intelligence Data processing ; Artificial intelligence Computer programs ; Python (Computer program language) ; Cloud computing ; Intelligence artificielle ; Informatique ; Intelligence artificielle ; Logiciels ; Python (Langage de programmation) ; Infonuagique ; Electronic books ; Natürliche Sprache ; Deep learning
    Abstract: Transformers are a game-changer for natural language understanding (NLU) and have become one of the pillars of artificial intelligence. Transformers for Natural Language Processing, 2nd Edition, investigates deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question-answering, and many more NLP domains with transformers. An Industry 4.0 AI specialist needs to be adaptable; knowing just one NLP platform is not enough anymore. Different platforms have different benefits depending on the application, whether it's cost, flexibility, ease of implementation, results, or performance. In this book, we analyze numerous use cases with Hugging Face, Google Trax, OpenAI, and AllenNLP. This book takes transformers' capabilities further by combining multiple NLP techniques, such as sentiment analysis, named entity recognition, and semantic role labeling, to analyze complex use cases, such as dissecting fake news on Twitter. Also, see how transformers can create code using just a brief description. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models to various datasets.
    Note: Includes index
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    Deep learning with Keras : implement neural networks with Keras on Theano and TensorFlow (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787129030 , 1787129039
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Neural networks (Computer science) ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Get to grips with the basics of Keras to implement fast and efficient deep-learning models About This Book Implement various deep-learning algorithms in Keras and see how deep-learning can be used in games See how various deep-learning models and practical use-cases can be implemented using Keras A practical, hands-on guide with real-world examples to give you a strong foundation in Keras Who This Book Is For If you are a data scientist with experience in machine learning or an AI programmer with some exposure to neural networks, you will find this book a useful entry point to deep-learning with Keras. A knowledge of Python is required for this book. What You Will Learn Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm Fine-tune a neural network to improve the quality of results Use deep learning for image and audio processing Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases Identify problems for which Recurrent Neural Network (RNN) solutions are suitable Explore the process required to implement Autoencoders Evolve a deep neural network using reinforcement learning In Detail This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GAN). You will also explore non-traditional uses of neural networks as Style Transfer. Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks. Style and approach This book is an easy-to-follow guide full of examples and real-world applications to help you gain an in-depth understanding of Keras. This book will showcase more than twenty working Deep Neural Networks coded in Python using Keras. Downloading the example code for thi...
    Note: Description based on online resource; title from title page (Safari, viewed May 15, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787128422/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    TensorFlow 1.x deep learning cookbook : over 90 unique recipes to solve artificial-intelligence driven problems with Python (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788291866 , 1788291867
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    RVK:
    ST 300
    Keywords: Machine learning ; Artificial intelligence ; Python (Computer program language)
    Note: Description based on online resource; title from title page (Safari, viewed January 23, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788293594/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Deep learning with TensorFlow and Keras (2022)
    Birmingham, UK : Packt Publishing Ltd.
    Details
    ISBN: 9781803232911
    Language: English
    Pages: 1 online resource (698 pages) , illustrations
    Edition: Third edition.
    Series Statement: Expert insight
    DDC: 005.13/3
    Keywords: TensorFlow ; Machine learning ; Artificial intelligence ; Neural networks (Computer science) ; Python (Computer program language)
    Abstract: Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML.
    Note: Includes bibliographical references and index
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 7
    Online Resource
    Online Resource
    Google Anthos in action : manage hybrid and multicloud Kubernetes clusters (2023)
    [Place of publication not identified] : Manning Publications
    Details
    Language: English
    Pages: 1 online resource (1 sound file (19 hr., 56 min.))
    Edition: [First edition].
    DDC: 004.67/82
    Keywords: Kubernetes ; Cloud computing ; Infonuagique ; Audiobooks ; Livres audio
    Abstract: Learn multicloud deployment on Anthos directly from the Google development team! Anthos delivers a consistent management platform for deploying and operating Linux and Windows applications anywhere--multi-cloud, edge, on-prem, bare metal, or VMware. In Google Anthos in Action you will learn: How Anthos reduces your dependencies and stack-bloat Running applications across multiple clouds and platforms Handling different workloads and data Adding automation to speed up code delivery Modernizing infrastructure with microservices and Service Mesh Policy management for enterprises Security and observability at scale Google Anthos in Action demystifies Anthos with practical examples of Anthos at work and invaluable insights from the Google team that built it. You'll learn how to use this modern, Kubernetes-based cloud platform to balance costs, automate security, and run your software literally anywhere. The book is full of Google-tested patterns that will boost efficiency across the development lifecycle. It's an absolutely essential guide for anyone working with Anthos, or delivering software in a cloud-centric world. About the Technology The operations nightmare: modern applications run on-prem, in the cloud, at the edge, on bare metal, in containers, over VMs, in any combination. And you're expected to handle the rollouts, dataOps, security, performance, scaling, backup, and whatever else comes your way. Google Anthos feels your pain. This Kubernetes-based system simplifies hybrid and multicloud operations, providing a single platform for deploying and managing your applications, wherever they live. About the Book Google Anthos in Action introduces Anthos and shows you how it can simplify operations for hybrid cloud systems. Written by 17 Googlers, it lays out everything you can do with Anthos, from Kubernetes deployments to AI models and edge computing. Each fully illustrated chapter opens up a different Anthos feature, with exercises and examples so you can see Anthos in action. You'll appreciate the valuable mix of perspectives and insight this awesome team of authors delivers. What's Inside Reduce dependencies and stack-bloat Run applications across multiple clouds and platforms Speed up code delivery with automation Policy management for enterprises Security and observability at scale About the Reader For software and cloud engineers with experience using Kubernetes. About the Author Google Anthos in Action is written by a team of 17 Googlers involved with Anthos development, and Google Cloud Certified Fellows assisting customers in the field. Quotes Your guide into the world of multicloud at scale. A great read whether you are just starting out or a seasoned veteran. - Glen Yu, PwC Canada Great book for engineers who want to learn Anthos. - Bhagvan Kommadi, Quantica Computacao Google Anthos can be intimidating. This book is an essential guide to using and understanding it. - Jose San Leandro, ioBuilders Complete, easy to understand, with simple explanations, useful diagrams, and real-world examples. I recommend it. - Rambabu Posa, Sai AAshika Consultancy.
    Note: Online resource; title from title details screen (O'Reilly, viewed February 19, 2024)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 8
    Online Resource
    Online Resource
    Chokkan Deep learning : Python×Keras de aidea o katachi ni suru reshipi (2018)
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Details
    Orig.schr. Ausgabe: 初版.
    Title: 直感 Deep learning : : Python×Kerasでアイデアを形にするレシピ /
    Publisher: オライリー・ジャパン,
    ISBN: 9784873118260 , 4873118263
    Language: Japanese
    Pages: 1 online resource (336 pages)
    Edition: Shohan.
    Uniform Title: Deep learning with Keras
    DDC: 005.133
    Keywords: Python (Computer program language) ; Neural networks (Computer science) ; Deep learning (Machine learning) ; Deep learning (Machine learning) ; Neural networks (Computer science) ; Python (Computer program language)
    Note: In Japanese.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 9
    Online Resource
    Online Resource
    Google Anthos in action : manage hybrid and multicloud Kubernetes clusters (2023)
    [Place of publication not identified] : Manning Publications
    Details
    Language: English
    Pages: 1 online resource (1 video file (20 hr., 16 min.)) , sound, color.
    Edition: [Video edition].
    DDC: 004.67/82
    Keywords: Kubernetes ; Cloud computing ; Infonuagique ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Learn multicloud deployment on Anthos directly from the Google development team! Anthos delivers a consistent management platform for deploying and operating Linux and Windows applications anywhere--multi-cloud, edge, on-prem, bare metal, or VMware. In Google Anthos in Action you will learn: How Anthos reduces your dependencies and stack-bloat Running applications across multiple clouds and platforms Handling different workloads and data Adding automation to speed up code delivery Modernizing infrastructure with microservices and Service Mesh Policy management for enterprises Security and observability at scale Google Anthos in Action demystifies Anthos with practical examples of Anthos at work and invaluable insights from the Google team that built it. You'll learn how to use this modern, Kubernetes-based cloud platform to balance costs, automate security, and run your software literally anywhere. The book is full of Google-tested patterns that will boost efficiency across the development lifecycle. It's an absolutely essential guide for anyone working with Anthos, or delivering software in a cloud-centric world. About the Technology The operations nightmare: modern applications run on-prem, in the cloud, at the edge, on bare metal, in containers, over VMs, in any combination. And you're expected to handle the rollouts, dataOps, security, performance, scaling, backup, and whatever else comes your way. Google Anthos feels your pain. This Kubernetes-based system simplifies hybrid and multicloud operations, providing a single platform for deploying and managing your applications, wherever they live. About the Book Google Anthos in Action introduces Anthos and shows you how it can simplify operations for hybrid cloud systems. Written by 17 Googlers, it lays out everything you can do with Anthos, from Kubernetes deployments to AI models and edge computing. Each fully illustrated chapter opens up a different Anthos feature, with exercises and examples so you can see Anthos in action. You'll appreciate the valuable mix of perspectives and insight this awesome team of authors delivers. What's Inside Reduce dependencies and stack-bloat Run applications across multiple clouds and platforms Speed up code delivery with automation Policy management for enterprises Security and observability at scale About the Reader For software and cloud engineers with experience using Kubernetes. About the Author Google Anthos in Action is written by a team of 17 Googlers involved with Anthos development, and Google Cloud Certified Fellows assisting customers in the field. Quotes Your guide into the world of multicloud at scale. A great read whether you are just starting out or a seasoned veteran. - Glen Yu, PwC Canada Great book for engineers who want to learn Anthos. - Bhagvan Kommadi, Quantica Computacao Google Anthos can be intimidating. This book is an essential guide to using and understanding it. - Jose San Leandro, ioBuilders Complete, easy to understand, with simple explanations, useful diagrams, and real-world examples. I recommend it. - Rambabu Posa, Sai AAshika Consultancy.
    Note: Online resource; title from title details screen (O'Reilly, viewed February 27, 2024)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
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