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  • 1
    Online Resource
    Online Resource
    Python深度学习入门： 从零构建CNN和RNN (2021)
    [Erscheinungsort nicht ermittelbar] : Posts & Telecom Press | Boston, MA : Safari
    Details
    ISBN: 9787115555649
    Language: English , Chinese
    Pages: 1 online resource (214 pages)
    Edition: 1st edition
    Keywords: Electronic books
    Abstract: 深度学习技术的发展如火如荼，这些知识正迅速成为机器学习从业者甚至许多软件开发工程师的“加分项”。深度学习是一个立体的领域，仅从数学层面或代码层面学习，难免以偏概全，无法融会贯通。 本书作者认为，理解深度学习和神经网络需要多种思维模型。因此，本书从数学、示意图、Python代码三个维度帮助你立体地理解每一个概念，带你领略深度学习领域的全貌，从内到外地理解构建神经网络的每一步。你将学到以下内容。 为理解深度学习的概念和原理构建多种思维模型。 掌握嵌套函数、链式法则等数学概念。 掌握学习率衰减、权重初始化、dropout等优化技巧。 从零构建CNN和RNN等常见的神经网络架构。 使用PyTorch实现神经网络。
    Note: Online resource; Title from title page (viewed February 1, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 2
    Online Resource
    Online Resource
    Deep Learning from Scratch (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (250 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way. Author Seth Weidman shows you how neural networks work using a first principles approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning projects. This book provides: Extremely clear and thorough mental models—accompanied by working code examples and mathematical explanations—for understanding neural networks Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework Working implementations and clear-cut explanations of convolutional and recurrent neural networks Implementation of these neural network concepts using the popular PyTorch framework
    Note: Online resource; Title from title page (viewed September 11, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492041405/?ar
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    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Deep Learning - Grundlagen und Implementierung (2020)
    [Erscheinungsort nicht ermittelbar] : dpunkt | Boston, MA : Safari
    Details
    Language: English , German
    Pages: 1 online resource (252 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Dieses Buch vermittelt Ihnen das konzeptionelle und praktische Rüstzeug, um ein tiefes Verständnis für die Funktionsweise neuronaler Netze zu bekommen. Sie lernen die Grundprinzipien des Deep Learning kennen, zu deren Veranschaulichung Seth Weidman gut nachvollziehbare Konzeptmodelle entwickelt hat, die von Codebeispielen begleitet werden. Das Buch eignet sich für Data Scientists und Softwareentwickler mit Erfahrung im Machine Learning.Sie beginnen mit den Basics des Deep Learning und gelangen schnell zu den Details fortgeschrittener Architekturen, indem Sie deren Aufbau von Grund auf neu implementieren. Dabei lernen Sie mehrschichtige neuronale Netze wie Convolutional und Recurrent Neural Networks kennen. Diese neuronalen Netzwerkkonzepte setzen Sie dann mit dem beliebten Framework PyTorch praktisch um. Auf diese Weise bauen Sie ein fundiertes Wissen darüber auf, wie neuronale Netze mathematisch, rechnerisch und konzeptionell funktionieren.
    Note: Online resource; Title from title page (viewed May 5, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 4
    Online Resource
    Online Resource
    Uczenie głębokie od zera (2020)
    [Erscheinungsort nicht ermittelbar] : Helion | Boston, MA : Safari
    Details
    ISBN: 9788328365971
    Language: English , Polish
    Pages: 1 online resource (224 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Ten praktyczny podręcznik, poświęcony podstawom uczenia głębokiego, zrozumiale i wyczerpująco przedstawia zasady działania sieci neuronowych z trzech różnych poziomów matematycznego, obliczeniowego i konceptualnego. Takie podejście wynika z faktu, że dogłębne zrozumienie sieci neuronowych wymaga nie jednego, ale kilku modeli umysłowych, z których każdy objaśnia inny aspekt działania tych sieci. Zaprezentowano tu również techniki implementacji poszczególnych elementów w języku Python, co pozwala utworzyć działające sieci neuronowe. Dzięki tej książce stanie się jasne, w jaki sposób należy tworzyć, uczyć i stosować wielowarstwowe, konwolucyjne i rekurencyjne sieci neuronowe w różnych praktycznych zastosowaniach.
    Note: Online resource; Title from title page (viewed May 26, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 5
    Online Resource
    Online Resource
    Deep learning (2023)
    [Erscheinungsort nicht ermittelbar] : Tecniche Nuove | Boston, MA : Safari
    Details
    ISBN: 9788848141130
    Language: English , Italian
    Pages: 1 online resource (264 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Negli ultimi dieci anni, con il ritorno delle reti neurali, la comprensione del Deep Learning è diventata essenziale e questo manuale fornisce un’introduzione approfondita per i data scientist e gli ingegneri del software con precedenti esperienze nel machine learning. Inizierete con le basi del Deep Learning e passerete rapidamente ai dettagli di importanti architetture avanzate, implementando tutto da zero. L’autore Seth Weidman vi mostra come funzionano le reti neurali usando un approccio basato su principi primi. Imparerete come applicare da zero le reti neurali multistrato, le reti neurali convoluzionali e quelle ricorrenti. Acquisendo una comprensione dettagliata di come queste reti funzionino matematicamente, computazionalmente e concettualmente, porterete a termine con successo i vostri futuri progetti di Deep Learning.
    Note: Online resource; Title from title page (viewed September 21, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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