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Data Science: Concepts and Practice
Gain the necessary knowledge of different data science techniques to extract value from data.
Data Science: Concepts and Practice
Item #: 227572170

Data Science: Concepts and Practice

Item #: 227572170

MAD 692

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Gain the necessary knowledge of different data science techniques to extract value from data.
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What Stands Out

Comprehensive Coverage
Thoroughly covers essential data science concepts, ensuring readers grasp theoretical and practical knowledge necessary for effective application in real-world scenarios.
Hands-On Practice
Incorporates practical exercises, reinforcing learning through active engagement, allowing learners to apply concepts and build confidence in their data science skills.
User-Friendly Approach
Structured layout with clear explanations makes complex topics accessible, catering to beginners while still providing depth for more experienced readers to enhance their expertise.

Product Details

Shop Data Science: Concepts and Practice online at a best price in Morocco. B07L29CY52
Publisher Morgan Kaufmann
Publication date November 27, 2018
Edition 2nd
Language English
File size 55.5 MB
Screen Reader Supported
Enhanced typesetting Enabled
X-Ray for textbooks Enabled
Word Wise Not Enabled
Print length 544 pages
ISBN-13 978-0128147627
Page Flip Enabled
Item Weight1.5 lbs (680 grams)

Product Description

Data Science: Concepts and Practice

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AI & Semantics Editorial Review

The product in review appears to be a textbook on Predictive Analytics that utilizes RapidMiner as its primary tool. Customers have generally found the book to be well-written, straightforward, and effective for those specifically looking to learn how to employ RapidMiner in their predictive analytics endeavors. While the book covers foundational concepts in data science, some users note that it may not be comprehensive enough for those seeking an in-depth understanding of the field, particularly in programming languages like R or Python. Feedback highlights the effectiveness of the book in teaching fundamental principles, with one reviewer praising its clarity and ease of understanding. This positions the textbook as an excellent resource for beginners or students needing to engage with predictive analytics in a practical context, albeit with the understanding that it may serve best as a supplement rather than a standalone data science curriculum. **

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Pros

  • Comprehensive coverage of using RapidMiner for predictive analytics.
  • Well-written and easy to understand, making it accessible for beginners.
  • Provides a solid foundation in the principles of data science.

Cons

  • Not a deep dive into data science; may not suffice for advanced learning.

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