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Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch
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Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch
Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch
Vare #: 83394025

Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch

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Hvad der skiller sig ud

Hands-On Approach
Delivers practical techniques for implementing graph neural networks, enabling readers to gain real-world experience and apply their knowledge in actual projects effectively.
PyTorch Integration
Leveraging PyTorch's capabilities, it simplifies deep learning development while providing robust frameworks and tools tailored for graph-based modeling, making it accessible for developers at all levels.
Comprehensive Coverage
Covers a wide range of architectures and applications, equipping readers with a thorough understanding of graph neural networks to tackle diverse problems in various domains.

Produktdetaljer

Shop Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch online at a best price in Greenland. 1804617520
Publisher Packt Publishing
Publication date April 14, 2023
Edition 1st
Language English
Print length 354 pages
ISBN-10 1804617520
ISBN-13 978-1804617526
Item Weight 1.43 pounds (650 grams)
Dimensions 7.5 x 0.8 x 9.25 inches (19.1 x 2 x 23.5 cm)

Hvem bør købe?

Suitable For
  • Data Scientists

    Ideal for data scientists looking to leverage graph neural networks for advanced data analysis and modeling tasks.

  • Machine Learning Developers

    Great for developers who want to build deep learning applications using PyTorch, specifically focusing on graph structures.

  • Students in AI

    Perfect for students seeking practical guidance on graph neural networks and deep learning in an educational format.

Not Suitable For
  • Beginners in Programming

    Not suitable for absolute beginners who lack basic programming knowledge or experience with Python and machine learning.

Produktbeskrivelse

Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch

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Intelligence & Semantics Editorial Review

The book "Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch" provides a good overview of the approaches and techniques used in graph neural networks. It also serves as a helpful introduction to the packages available for GNNs in Python. However, some weaknesses were identified in the reviews, such as the lack of detailed implementation explanations, glossing over key concepts, and not delving into why GNNs work better than other techniques in-depth. The book is noted for its clear explanations and functioning examples, making it suitable for individuals with basic ML/DL knowledge looking to delve into GNNs. While the physical book is of good quality, some readers found it cumbersome to use, suggesting opting for the free PDF version for a better reading experience. **

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Fordele

  • Great overview of GNN approaches and techniques
  • Good introduction to Python packages for GNNs
  • Clear explanations and functioning examples

Ulemper

  • Lack of detailed implementation explanations

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