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Data Science: Concepts and Practice
Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations.
Data Science: Concepts and Practice
Item #: 17398483

Data Science: Concepts and Practice

Item #: 17398483

SAR 263

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    Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations.
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    What Stands Out

    Comprehensive Coverage
    Covers essential data science concepts and practical applications, providing a solid foundation for beginners and advanced learners alike. This makes it an ideal resource for both academic and professional growth.
    Hands-on Approach
    Includes practical exercises and real-world case studies that help readers apply theoretical knowledge. This enhances understanding and ensures learners can tackle actual data science challenges.
    Updated Content
    Features the latest trends and technologies in data science, ensuring relevance in a rapidly evolving field. This equips readers with current knowledge and skills applicable in today’s job market.

    Product Details

    Discover the key concepts and practical applications of data science with Data Science: Concepts and Practice 2nd Edition. Order now from Ubuy, a Saudi Arabia.
    Publisher Morgan Kaufmann
    Publication date December 21, 2018
    Edition 2nd
    Language English
    Print length 568 pages
    ISBN-10 012814761X
    ISBN-13 978-0128147610
    Item Weight 2.5 pounds (1.13 kg)
    Dimensions 7.52 x 1.28 x 9.25 inches (19.1 x 3.3 x 23.5 cm)

    Who Should Buy?

    Suitable For
    • Aspiring Data Scientists

      Ideal for newcomers seeking foundational knowledge in data science concepts and practical applications.

    • Students in Academia

      Suitable for college students enrolled in data science or related programs, providing comprehensive material for coursework.

    • Professionals Upskilling

      Great for industry professionals looking to upgrade their skills and understanding of data science methodologies.

    Not Suitable For
    • Advanced Practitioners

      Not suitable for experienced data scientists seeking deeper or more advanced theoretical knowledge.

    Product Description

    Data Science: Concepts and Practice

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    Intelligence & Semantics Editorial Review

    The "RapidMiner Data Science Use Cases" textbook is receiving generally positive reviews from customers, specifically from those using it as a resource for predictive analytics. Users have noted that the book covers all the necessary aspects of the RapidMiner application, making it a valuable tool for understanding data science concepts. While some users found the book to be a good starting point for learning data science, others felt that it may not be comprehensive enough for those looking for more in-depth knowledge in the field. One reviewer highlighted the importance of color in illustrations, suggesting that the book's use of grayscale images could be improved. However, despite this minor drawback, many users found the content of the book to be informative and practical for their needs. The book covers various data science models and emphasizes the four key skills required for effective analytics: business understanding, data understanding, software understanding, and data science understanding. Overall, the "RapidMiner Data Science Use Cases" textbook is recommended for individuals seeking an introduction to data science, especially for students and professionals who are not aiming to specialize in the field. The book's coverage of RapidMiner and data science models, combined with its straightforward and comprehensive approach, make it a worthwhile investment for those looking to enhance their understanding of predictive analytics. **

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    Pros

    • Comprehensive coverage of RapidMiner and data science concepts
    • Practical and informative content for beginners and non-specialists
    • Emphasis on key skills required for effective analytics

    Cons

    • Grayscale illustrations may hinder comprehension for some readers

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