Xu Kele (18 results)

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering.

Taschenbuch. Condition: Neu. Data Mining Competition Practices | Methods and Cases | Kele Xu | Taschenbuch | xii | Englisch | 2026 | Springer | EAN 9789819534456 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Hardcover. Condition: new. Hardcover. Dive into the cutting-edge integration of deep learning with audio signal processing in this authoritative guide. Designed for audio engineers, data scientists, and tech enthusiasts, this book demystifies the complex world of deep neural networks, including CNNs and RNNs, and their applications in speech recognition, music transcription, and sound event detection.Explore the practical side of deep learning with hands-on tutorials using TensorFlow and PyTorch, building your intuition for model architectures and hyperparameter tuning. Gain insights into real-world deployment challenges, from data preprocessing to model evaluation, interpretability, and scalability. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Whether you're a researcher, engineer, or enthusiast, this guide is your key to mastering the synergy of audio signal processing and deep learning, ensuring you approach audio-related challenges with confidence and proficiency. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condition: new. Hardcover. Dive into the cutting-edge integration of deep learning with audio signal processing in this authoritative guide. Designed for audio engineers, data scientists, and tech enthusiasts, this book demystifies the complex world of deep neural networks, including CNNs and RNNs, and their applications in speech recognition, music transcription, and sound event detection.Explore the practical side of deep learning with hands-on tutorials using TensorFlow and PyTorch, building your intuition for model architectures and hyperparameter tuning. Gain insights into real-world deployment challenges, from data preprocessing to model evaluation, interpretability, and scalability. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Whether you're a researcher, engineer, or enthusiast, this guide is your key to mastering the synergy of audio signal processing and deep learning, ensuring you approach audio-related challenges with confidence and proficiency. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condition: New.

Hardcover. Condition: new. Hardcover. Dive into the cutting-edge integration of deep learning with audio signal processing in this authoritative guide. Designed for audio engineers, data scientists, and tech enthusiasts, this book demystifies the complex world of deep neural networks, including CNNs and RNNs, and their applications in speech recognition, music transcription, and sound event detection.Explore the practical side of deep learning with hands-on tutorials using TensorFlow and PyTorch, building your intuition for model architectures and hyperparameter tuning. Gain insights into real-world deployment challenges, from data preprocessing to model evaluation, interpretability, and scalability. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Whether you're a researcher, engineer, or enthusiast, this guide is your key to mastering the synergy of audio signal processing and deep learning, ensuring you approach audio-related challenges with confidence and proficiency. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims to provide readers with a clear implementation process for data mining competition solutions and explains the key details involved. In addition to offering the necessary theoretical knowledge, it also provides plug-and-play code. By reading this book, readers will learn how to design a solution for a data mining competition, understand the various details and specific implementation methods of the solution, and learn how to continually refine and optimize it. The book also includes practical case studies to help readers grasp and reinforce these concepts. Data mining competitions offer datasets that closely resemble real-world scenarios, making this book an excellent choice for those who want to learn data mining techniques through hands-on practice.At the same time, this book can also serve as a reference guide, providing various methods and techniques for the entire process from data input to obtaining final results in different scenarios, including structured data, natural language processing, computer vision, video understanding, and reinforcement learning. These practical methods and techniques can help readers significantly improve their performance on datasets and are applicable not only in data mining competitions but also in research and real-world business applications.The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content. 243 pp. Englisch.…

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Condition: New. PRINT ON DEMAND.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 256 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Dive into the cutting-edge integration of deep learning with audio signal processing in this authoritative guide. Designed for audio engineers, data scientists, and tech enthusiasts, this book demystifies the complex world of deep neural networks, including CNNs and RNNs, and their applications in speech recognition, music transcription, and sound event detection.Explore the practical side of deep learning with hands-on tutorials using TensorFlow and PyTorch, building your intuition for model architectures and hyperparameter tuning. Gain insights into real-world deployment challenges, from data preprocessing to model evaluation, interpretability, and scalability. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Whether you're a researcher, engineer, or enthusiast, this guide is your key to mastering the synergy of audio signal processing and deep learning, ensuring you approach audio-related challenges with confidence and proficiency. 676 pp. Englisch.…

Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Dive into the cutting-edge integration of deep learning with audio signal processing in this authoritative guide. Designed for audio engineers, data scientists, and tech enthusiasts, this book demystifies the complex world of deep neural networks, including CNNs and RNNs, and their applications in speech recognition, music transcription, and sound event detection.Explore the practical side of deep learning with hands-on tutorials using TensorFlow and PyTorch, building your intuition for model architectures and hyperparameter tuning. Gain insights into real-world deployment challenges, from data preprocessing to model evaluation, interpretability, and scalability. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Whether you're a researcher, engineer, or enthusiast, this guide is your key to mastering the synergy of audio signal processing and deep learning, ensuring you approach audio-related challenges with confidence and proficiency.Springer Nature Customer Service Center GmbH, Europaplatz 3,69115 Heidelberg, Germany, Heidelberg 716 pp. Englisch.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Dive into the cutting-edge integration of deep learning with audio signal processing in this authoritative guide. Designed for audio engineers, data scientists, and tech enthusiasts, this book demystifies the complex world of deep neural networks, including CNNs and RNNs, and their applications in speech recognition, music transcription, and sound event detection.Explore the practical side of deep learning with hands-on tutorials using TensorFlow and PyTorch, building your intuition for model architectures and hyperparameter tuning. Gain insights into real-world deployment challenges, from data preprocessing to model evaluation, interpretability, and scalability. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Whether you're a researcher, engineer, or enthusiast, this guide is your key to mastering the synergy of audio signal processing and deep learning, ensuring you approach audio-related challenges with confidence and proficiency.…

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.