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Item #:
91791440
Practical Business Analytics Using R and Python: Solve Business Problems Using a Data-driven Approach
88% of respondents would recommend this to a friend
Item #:
91791440
€ 43
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Understand various analytics models and data mining techniques such as regression, supervised machine learning algorithms for modeling, unsupervised modeling techniques, and how to choose the correct algorithm for analysis in any given task.
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What Stands Out
Dual Programming Focus
Combines R and Python, enabling readers to leverage both programming languages for diverse analytical needs, equipping them with a broad skill set to tackle various business challenges effectively.
Data-Driven Approach
Emphasizes practical, data-driven methodologies that address real-world business problems, providing actionable insights that enhance decision-making and foster strategic planning for organizations.
Updated Content
Second edition includes the latest trends and best practices in business analytics, ensuring readers are well-informed about current tools and techniques vital for successful analytics implementation.
Product Details
| Publisher | Apress |
| Publication date | April 4, 2023 |
| Edition | Second |
| Language | English |
| Print length | 731 pages |
| ISBN-10 | 1484287533 |
| ISBN-13 | 978-1484287538 |
| Item Weight | 2.8 pounds (1.27 kg) |
| Dimensions | 7 x 1.5 x 10 inches (17.8 x 3.8 x 25.4 cm) |
Who Should Buy?
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Data Analysts
Ideal for data analysts seeking to enhance their skills in R and Python for business analytics applications.
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Business Students
Beneficial for business students wanting to understand practical applications of data analytics in real-world scenarios.
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Industry Professionals
Useful for professionals in business roles looking to leverage data analytics to inform decision-making processes.
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Beginners
Not suitable for complete beginners without prior knowledge of R, Python, or data analytics principles.
Product Description
Practical Business Analytics Using R and Python: Solve Business Problems Using a Data-driven Approach
Have any Query? Chat with us
Customer Questions & Answers
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Question:
Who is this book intended for?
Answer: It is designed for software professionals, managers, and executives interested in learning business analytics using R and Python. -
Question:
What programming languages are covered in the book?
Answer: The book includes practical insights using both R and Python for data analytics. -
Question:
What analytics concepts will I learn?
Answer: You will learn about regression models, supervised and unsupervised machine learning, clustering, and natural language processing.
Intelligence & Semantics Editorial Review
**** "Practical Business Analytics Using R and Python: Solve Business Problems Using a Data-driven Approach" (2nd Edition) has received enthusiastic praise from various users, highlighting its effectiveness as both an educational resource and a practical guide. Reviewers from academia and the business analytics field commend the book for its comprehensive coverage of essential topics relevant to data analysts. The use of real-world examples, coupled with clear explanations and practical code snippets in R and Python, makes it a vital asset for both novice learners and experienced professionals. Many users emphasized how the book simplifies complex concepts in data manipulation, visualization, and predictive modeling, making them more approachable. This hands-on approach, particularly through the use of popular libraries like Pandas and Scikit-Learn, allows users to apply their knowledge directly to real business scenarios. The book is recommended not just as a textbook for classroom use but also for self-study, reflecting its versatility. With the author, Dr. Umesh, being recognized for his expertise in the field, there's a commendable appreciation for the author's ability to present intricate analytical topics in an accessible manner. The structured organization of the content further enhances its appeal, catering to a wide audience with varying levels of expertise. Overall, "Practical Business Analytics Using R and Python" comes across as a highly valued resource in the business analytics domain, fostering a robust understanding of data-driven problem-solving. **
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Pros
- Clear explanations of complex concepts
- Hands-on approach with practical code examples in R and Python
- Comprehensive coverage of relevant business analytics topics
- Suitable for both beginners and experienced analysts
- Well-organized content that facilitates learning and application
- Useful for classroom teaching and self-study
Cons
- No notable Cons have been mentioned in the reviews.
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€ 43
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Features & Benefits
- Master business analytics foundations for impactful decision-making.
- Learn predictive and unsupervised modeling techniques using R and Python.
- Discover how to interpret analytical model outcomes for actionable insights.
- Explore database management, SQL, and natural language processing in-depth.
- Utilize statistical machine learning concepts for better business outcomes.
- Ideal for software professionals, managers, and executives eager to grasp analytics.
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