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Modern Graph Theory Algorithms with Python: Harness the power of graph algorithms and real-world network applications using Python
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Modern Graph Theory Algorithms with Python: Harness the power of graph algorithms and real-world network applications using Python
By the end of this book, you’ll be well-equipped to wrangle your own datasets into network science problems and scale solutions with Python.
Modern Graph Theory Algorithms with Python: Harness the power of graph algorithms and real-world network applications using Python
物品 #: 113256517

Modern Graph Theory Algorithms with Python: Harness the power of graph algorithms and real-world network applications using Python

90% of respondents would recommend this to a friend

物品 #: 113256517

HKD 465

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By the end of this book, you’ll be well-equipped to wrangle your own datasets into network science problems and scale solutions with Python.
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What Stands Out

Practical Applications
Learn to implement real-world network and graph algorithms, making complex theoretical concepts accessible and applicable to everyday problems.
Python Integration
Seamlessly integrates Python with graph theory, enabling users to leverage familiar coding practices while exploring advanced algorithms and techniques.
Comprehensive Coverage
Offers a complete exploration of modern graph algorithms, ensuring that learners from beginner to advanced levels can enhance their skills drastically.

產品詳情

Shop Modern Graph Theory Algorithms with Python: Harness the power of graph algorithms and real-world network applications using Python online at a best price in 香港. 1805127896
Publisher Packt Publishing
Publication date June 7, 2024
Language English
Print length 290 pages
ISBN-10 1805127896
ISBN-13 978-1805127895
Item Weight 1.11 pounds (500 grams)
Dimensions 7.5 x 0.66 x 9.25 inches (19.1 x 1.7 x 23.5 cm)

Who Should Buy?

Suitable For
  • Data Scientists

    Ideal for data scientists looking to apply graph algorithms to solve complex data problems using Python.

  • Software Engineers

    Beneficial for software engineers needing to implement and optimize graph algorithms in real-world applications.

  • Students

    Suitable for students studying computer science or mathematics who want to gain practical experience in graph theory.

Not Suitable For
  • Beginners

    Not suitable for beginners with no prior programming or graph theory knowledge, as it may be too advanced.

產品敘述

Modern Graph Theory Algorithms with Python: Harness the power of graph algorithms and real-world network applications using Python

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Intelligence & Semantics Editorial Review

** Modern Graph Theory Algorithms with Python** "Modern Graph Theory Algorithms with Python" by Colleen M. Farrelly and Franck Kalala Mutombo offers a compelling exploration of graph theory tailored for both novice and experienced readers in the field of data science. With a clear structure that transitions from fundamental concepts to more sophisticated algorithms, the authors succeed in demystifying graph theory and demonstrating its real-world applications. Key strengths of the book lie in its comprehensive coverage of various topics and the seamless integration of Python as a practical tool for implementing graph algorithms. Readers are introduced to essential resources such as NetworkX, setting a strong foundation for hands-on learning. Engaging narratives accompany the high-quality illustrations, enriching the overall learning experience and igniting curiosity about the myriad applications of graph theory, from social networks to predictive analytics in finance and public health. The book’s practical approach is further enhanced by articulated case studies that showcase how network science can address contemporary issues, including the spread of misinformation or optimizing logistics. This broad scope not only educates but also encourages readers to think critically about how to apply graph theory to their specific challenges. However, while the book provides a solid introduction and insights into numerous applications, some readers might find that advanced topics are not covered in the depth they may desire. Additionally, the prerequisite knowledge of Python is assumed, which might be a barrier for absolute beginners. Overall, "Modern Graph Theory Algorithms with Python" is an essential addition to any data scientist's library, offering a compelling mix of theory, practice, and application in the dynamic realm of graph theory. **

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優點

  • Comprehensive coverage of graph theory concepts and algorithms.
  • Clear and accessible writing style suitable for various expertise levels.
  • Practical applications illustrated through engaging case studies.
  • Hands-on approach with Python implementations, leveraging library support like NetworkX.
  • Encourages critical thinking and exploration of real-world data challenges.

缺點

  • Some advanced topics may lack in-depth exploration.

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HKD 465

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特色和優勢

  • Learn to transform diverse datasets into network structures.
  • Utilize graph algorithms to analyze and visualize data efficiently.
  • Tackle real-world problems with hands-on case studies in Python.
  • Master tools for predicting trends like fake news and stock market crashes.
  • Enhance data analysis with advanced techniques like GNNs and graph databases.
  • Ideal for researchers and professionals eager to leverage network science.

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