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Data Science: Concepts and Practice
87% of respondents would recommend this to a friend
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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
Product Details
| 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?
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Aspiring Data Scientists
Ideal for newcomers seeking foundational knowledge in data science concepts and practical applications.
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Students in Academia
Suitable for college students enrolled in data science or related programs, providing comprehensive material for coursework.
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Professionals Upskilling
Great for industry professionals looking to upgrade their skills and understanding of data science methodologies.
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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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Features & Benefits
- 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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