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  1. Deep learning mit R und Keras : Das Praxis-Handbuch : von Entwicklern von Keras und RStudio

    Chollet, François
    1. Auflage. - [Frechen] : Mitp Verlags, [2018]

    Einführung in die grundlegenden Konzepte von Machine Learning und Deep Learning Zahlreiche praktische Anwendungsbeispiele zum Lösen konkreter Aufgabenstellungen: Maschinelles Sehen, Sprachverarbeitung, Bildklassifizierung, Vorhersage von Zeitreihen, Stimmungsanalyse CNNs, Rekurrente neuronale Netze, generative Modelle wie Variational Autoencoder und Generative-Adversarial-Netze Dieses Buch ist eine praxisorientierte Einführung und erläutert die grundlegenden Konzepte sowie den konkreten Einsatz von Deep Learning. Der Autor verzichtet dabei weitgehend auf mathematische Formeln und legt stattdessen den Fokus auf das Vermitteln der praktischen Anwendung von Machine Learning und Deep Learning. Anhand zahlreicher Beispiele erfahren Sie alles, was Sie benötigen, um Deep Learning zum Lösen konkreter Aufgabenstellungen einzusetzen. Dafür verwendet der Autor die Programmiersprache R und die Deep-Learning-Bibliothek Keras, die das beliebteste und am besten geeignete Tool für den Einstieg in Deep Learning ist. Das Buch besteht aus zwei Teilen: Teil I ist eine allgemeine Einführung in das Deep Learning und erläutert die grundlegenden Zusammenhänge und Begriffe sowie alle erforderlichen Konzepte, die für den Einstieg in Deep Learning und Neuronale Netze wichtig sind. In Teil II erläutert der Autor ausführlich die praktischen Anwendungen des Deep Learnings beim maschinellen Sehen (Computer Vision) und bei der Verarbeitung natürlicher Sprache. Viele der hier vorgestellten Beispiele können Ihnen später als Vorlage zum Lösen von Problemen dienen, die Ihnen in der Praxis des Deep Learnings begegnen werden. Das Buch wendet sich an Leser, die bereits Programmiererfahrung mit R haben und die ins Machine Learning und Deep Learning einsteigen möchten. Für den Einsatz von Keras werden grundlegende R-Kenntnisse vorausgesetzt.

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  2. Deep learning with Python video edition

    Chollet, François
    [Place of publication not identified] : Manning Publications, 2017.

    "Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning--a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications."--Resource description page.

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  3. Deep learning with R

    Chollet, François
    Second edition. - Shelter Island, NY : Manning Publications Co., [2022]

    Deep Learning with R, Second Edition shows you how to put deep learning into action. It’s based on the revised new edition of François Chollet’s bestselling Deep Learning with Python. All code and examples have been expertly translated to the R language by Tomasz Kalinowski, who maintains the Keras and Tensorflow R packages at RStudio. Novices and experienced ML practitioners will love the expert insights, practical techniques, and important theory for building neural networks.Deep learning from the ground up using R and the powerful Keras library! In Deep Learning with R, Second Edition you will learn: Deep learning from first principles Image classification and image segmentation Time series forecasting Text classification and machine translation Text generation, neural style transfer, and image generation Deep Learning with R, Second Edition shows you how to put deep learning into action. It's based on the revised new edition of Francois Chollet's bestselling Deep Learning with Python. All code and examples have been expertly translated to the R language by Tomasz Kalinowski, who maintains the Keras and Tensorflow R packages at RStudio. Novices and experienced ML practitioners will love the expert insights, practical techniques, and important theory for building neural networks. about the technology Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R. what's inside Image classification and image segmentation Time series forecasting Text classification and machine translation Text generation, neural style transfer, and image generation about the reader For readers with intermediate R skills. No previous experience with Keras, TensorFlow, or deep learning is required. .

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