Data Science: Concepts and Practice
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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
Numéro d'article: 17398483

Data Science: Concepts and Practice

90% des répondants recommanderaient ceci à un ami

Numéro d'article: 17398483

XAF 42084

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Ce qui se démarque

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.

Détails du produit

Discover the key concepts and practical applications of data science with Data Science: Concepts and Practice 2nd Edition. Order now from Ubuy, a Chad.
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)

À qui est-ce destiné ?

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.

DESCRIPTION DU PRODUIT

Data Science: Concepts and Practice

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Questions et réponses des clients

  • question: What topics are covered in Data Science: Concepts and Practice 2nd Edition?

    répondre: Data Science: Concepts and Practice 2nd Edition provides a comprehensive overview of critical topics in data science. It covers data analysis, statistical methods, machine learning algorithms, and practical applications, making it suitable for beginners and advanced learners. The book also emphasizes real-world case studies, illustrating how data science concepts apply in various domains such as healthcare, finance, and marketing. This multifaceted approach enables readers to grasp theoretical concepts while witnessing their practical implementation.
  • question: Is Data Science: Concepts and Practice 2nd Edition suitable for beginners?

    répondre: Yes, this edition is designed to cater to readers at all skill levels, including beginners. The authors introduce fundamental concepts gradually, allowing novice learners to build a solid foundation in data science. The book includes clear explanations, examples, and exercises to reinforce learning, making it a practical choice for self-study. Many users have positively highlighted how approachable the language and structure are, which aids in understanding complex topics without feeling overwhelmed.
  • question: Does the book include practical exercises or case studies?

    répondre: Absolutely! Data Science: Concepts and Practice 2nd Edition features numerous practical exercises and case studies throughout. These elements encourage hands-on application of the concepts discussed. Readers can engage with real datasets and scenarios, which enhances their problem-solving skills and analytical thinking. This experiential learning approach is particularly beneficial for those looking to transition into a professional data science role or improve their existing knowledge through practice.
  • question: Who is the target audience for this book?

    répondre: The target audience for Data Science: Concepts and Practice 2nd Edition includes students, professionals, and anyone eager to learn about data science. It serves as an educational resource for university courses as well as a practical guide for industry practitioners. Whether you are a data analyst, a researcher, or simply someone interested in the field, this book equips you with essential knowledge and skills needed to succeed in data-driven environments.
  • question: Are there supplementary resources available with the book?

    répondre: Yes, this edition often comes with several supplementary resources, such as online materials, datasets for practice, and interactive tools. These resources complement the textual content and enhance the learning experience by providing additional context and practice opportunities. Readers have found this bonus content incredibly helpful for reinforcing their understanding and applying concepts in authentic situations, making the learning journey more dynamic and engaging.
  • question: What distinguishes the 2nd edition from the previous one?

    répondre: The 2nd edition of Data Science: Concepts and Practice introduces updated content that reflects the latest trends and advancements in data science. This includes new sections on emerging technologies, refined algorithms, and updated case studies based on recent industry developments. Readers benefit from the authors’ inclusivity of contemporary challenges and practices, ensuring that the knowledge gained is relevant and applicable in today's rapidly evolving data landscape.
  • question: Can this book help with career development in data science?

    répondre: Certainly! Data Science: Concepts and Practice 2nd Edition equips readers with the technical and analytical skills that are crucial for career advancement in data science. Practical applications, industry-relevant examples, and a focus on critical thinking prepare readers for real-world challenges. Users often report that the book contributes significantly to their confidence in interviews and practical scenarios, making it an invaluable asset for anyone pursuing a career in this field.
  • question: Is statistical knowledge required to understand the content?

    répondre: While a basic understanding of statistics can be helpful, it is not mandatory to comprehend the content of Data Science: Concepts and Practice 2nd Edition. The authors introduce statistical concepts progressively and provide clear explanations to ensure that readers without a statistical background can follow along. This accessibility makes it a suitable resource for individuals at various educational backgrounds, allowing them to learn at their own pace while developing essential skills.
  • question: What makes this book a good choice for academic courses?

    répondre: Data Science: Concepts and Practice 2nd Edition reinforces academic concepts with a well-structured curriculum that is suitable for university-level courses. Its comprehensive coverage of theory and practical applications aligns with educational standards in data science and analytics. Faculty members often recommend it for course syllabi due to its clarity, in-depth exploration of key topics, and the inclusion of exercises that promote critical thinking and group discussions among students.
  • question: Where can I buy Data Science: Concepts and Practice 2nd Edition in Chad?

    répondre: You can purchase Data Science: Concepts and Practice 2nd Edition from Ubuy. Ubuy provides a wide selection of books and offers convenient shopping options for customers in Chad. With user-friendly navigation and reliable service, Ubuy is a great choice for finding this edition and enjoying a smooth purchasing experience.

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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Avantages

  • 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

Les inconvénients

  • Grayscale illustrations may hinder comprehension for some readers

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Caractéristiques et avantages

  • Learn the basics of Data Science with an easy-to-understand conceptual framework
  • Practice using the RapidMiner platform for immediate hands-on experience
  • Ideal for beginners and experienced individuals in the field of data analysis
  • Gain knowledge of different data science techniques and algorithms
  • Implement data science processes using RapidMiner without the need for programming
  • Includes practical use cases and explanations for over twenty powerful data science techniques

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