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Mastering Large Datasets with Python: Parallelize and Distribute Your Python Code
Mastering Large Datasets with Python teaches you to write code that can handle datasets of any size.
Mastering Large Datasets with Python: Parallelize and Distribute Your Python Code
Vare #: 52844593

Mastering Large Datasets with Python: Parallelize and Distribute Your Python Code

Vare #: 52844593

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Mastering Large Datasets with Python teaches you to write code that can handle datasets of any size.
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Hvad der skiller sig ud

Parallel Processing Techniques
Learn to effectively utilize parallel processing to accelerate data analysis, enabling faster workflows and improved efficiency in handling large datasets with Python.
Comprehensive Coverage
This book provides in-depth guidance on mastering various distributed computing frameworks, giving readers the knowledge to tackle complex problems with scalable solutions using Python.
Practical Examples
Offers real-world scenarios and hands-on examples that illustrate concepts, allowing readers to apply their skills immediately to solve data-intensive challenges effectively.

Produktdetaljer

Learn how to parallelize and distribute Python code for large datasets. Get the first edition of Mastering Large Datasets with Python at Ubuy Danmark.
  • Teaches how to scale small projects using a functionally influenced approach to Python coding
  • Explores methods and built-in Python tools for clarity and scalability, including high-performing parallelism and distributed technologies
  • Includes abundant hands-on exercises to lock in essential skills for large-scale data science projects
  • Covers programming techniques for handling datasets of any size and scaling efficiently without codebase rewrites
  • Introduces tools like Hadoop, PySpark, and AWS S3 for processing massive distributed datasets
Publisher Manning
Publication date January 21, 2020
Edition First Edition
Language English
Print length 312 pages
ISBN-10 1617296236
ISBN-13 978-1617296239
Item Weight 1.15 pounds (520 grams)
Dimensions 7.38 x 0.7 x 9.25 inches (18.7 x 1.8 x 23.5 cm)

Hvem bør købe?

Suitable For
  • Data Scientists

    Ideal for data scientists who need to process and analyze large datasets efficiently using Python's parallelization features.

  • Software Engineers

    Beneficial for software engineers working on applications that require handling big data and optimizing performance in Python.

  • Students & Learners

    Great for students seeking to enhance their knowledge of Python in big data contexts and improve their coding skills.

Not Suitable For
  • Beginner Programmers

    Not suitable for those new to programming, as it assumes a fundamental understanding of Python before diving in.

Produktbeskrivelse

Mastering Large Datasets with Python: Parallelize and Distribute Your Python Code

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    svar: Ja, hos Ubuy Denmark er dette produkt tilgængeligt, så du kan handle til en rimelig pris.. Mastering Large Datasets with Python: Parallelize er ikke tilgængelig lokalt, men du kan stole på os med vores ekspresforsendelsestjenester.
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Data Modeling & Design Editorial Review

**Editorial Review of "Mastering Large Datasets with Python: Parallelize and Distribute Your Python Code"** "Mastering Large Datasets with Python" has garnered attention as a comprehensive guide for data professionals seeking to enhance their skills in managing and processing large datasets. Readers have praised the book for its thorough exploration of parallelization and distribution techniques, emphasizing the practical application of Python in handling extensive data operations efficiently. Customers have noted that the book strikes an excellent balance between theoretical knowledge and practical application. The inclusion of real-world examples and clear code snippets facilitates a better understanding of complex concepts. Many reviewers have appreciated the structured approach, which breaks down the intricate aspects of data handling into manageable sections. This layout is particularly beneficial for those new to the subject, allowing them to grasp advanced concepts without feeling overwhelmed. However, a few users expressed that certain sections could benefit from deeper explanations or additional case studies, especially for readers who may not have prior experience with parallel processing. Despite this, the feedback overwhelmingly highlights the utility of the book as a valued resource for anyone looking to work with large datasets in Python, from enthusiasts to seasoned professionals. In conclusion, "Mastering Large Datasets with Python" is effectively positioned as an essential text for individuals aiming to advance their Python skills in data manipulation. The positive reception surrounding its practical approach and clarity indicates that it has successfully met the needs of its target audience. **

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Fordele

  • Comprehensive coverage of parallelization and distribution in Python.
  • Strong balance of theory and practical application.
  • Clear explanations and well-structured chapters.
  • Includes real-world examples and code snippets for better understanding.

Ulemper

  • Some sections lack deeper explanations.

Produktets prishistorik

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