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Business Analytics with R and Python (AI for Risks)
INR 6971
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Unlock the power of data mining to tackle business challenges and elevate decision-making with 'Business Analytics with R and Python.'
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Product Details
- This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, descriptive analytics focuses on what has happened and predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 3 describes initial data visualization tools. Chapter 4 describes association rules and software support. Chapter 5 describes cluster analysis with software demonstration. Chapter 6 discusses time series analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Applications of the context of management are presented in Chapter 8. Chapter 9 covers prescriptive modeling in business and applications of artificial intelligence.
| Publisher | Springer |
| Publication date | July 30, 2024 |
| Language | English |
| File size | 32.7 MB |
| Enhanced typesetting | Enabled |
| X-Ray | Not Enabled |
| Word Wise | Not Enabled |
| Print length | 297 pages |
| ISBN-13 | 978-9819747726 |
| Page Flip | Enabled |
| Item Weight | 1.5 lbs (680 grams) |
Product Description
Business Analytics with R and Python (AI for Risks)
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INR 6971
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Features & Benefits
- Learn how to utilize data mining methods to improve customer service.
- Understand the role of descriptive and predictive analytics in business management.
- Access practical applications of analytic tools for real-world business scenarios.
- Explore initial data visualization techniques to enhance decision-making.
- Dive into advanced topics like cluster analysis and predictive classification.
- Leverage artificial intelligence to model prescriptive solutions for business challenges.
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