Practical applications of data processing, algorithms, and modeling:
"The book serves as a practical guide, providing hands-on examples, case studies, and problem-solving scenarios. It aims to empower readers to confidently navigate through data challenges and make informed decisions using data-driven insights"--
Saved in:
| Other Authors: | , , , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2024.
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | "The book serves as a practical guide, providing hands-on examples, case studies, and problem-solving scenarios. It aims to empower readers to confidently navigate through data challenges and make informed decisions using data-driven insights"-- |
| Physical Description: | 27 PDFs (313 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9798369329108 |
| Access: | Restricted to subscribers or individual electronic text purchasers. |
Staff View
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| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Chapter 1. Introduction to data processing: understanding the core concepts of data modeling -- Chapter 2. Machine learning mastery: practical insights for data processing -- Chapter 3. Algorithmic insights: exploring AI and ML in practical applications -- Chapter 4. Architecture, framework, and models for edge-AI in healthcare -- Chapter 5. AI-driven modeling: from concept to implementation -- Chapter 6. Agricultural insights: practical applications of data processing, algorithms, and modeling in farming -- Chapter 7. A novel online job scam detection of imbalanced data using ML and NLP models -- Chapter 8. Data analysis using IoT technologies for enhanced healthcare decision-making -- Chapter 9. Data privacy, compliance, and security including AI ML: healthcare -- Chapter 10. Data privacy, compliance, and security in cloud computing for finance -- Chapter 11. Demystifying machine learning by unraveling interpretability -- Chapter 12. Mastering data management: practical applications of data processing, algorithms, and modeling -- Chapter 13. Measuring psychometric analysis of stress level in learners across multiple parameters using machine learning -- Chapter 14. Navigating the essential fundamentals of data processing for modern enterprises -- Chapter 15. Optimizing with intelligence: harnessing AI and ML algorithms for real-world solutions -- Chapter 16. Smart data processing: unleashing the power of AI and ML -- Chapter 17. Unleashing the power of cloud computing for data science -- Chapter 18. Unveiling the frontiers: latest advancements in data science techniques and applications -- Chapter 19. Using complex network analysis techniques to uncover fraudulent activity in connected healthcare systems -- Chapter 20. Challenges and future directions in anomaly detection. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "The book serves as a practical guide, providing hands-on examples, case studies, and problem-solving scenarios. It aims to empower readers to confidently navigate through data challenges and make informed decisions using data-driven insights"-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 05/17/2024). | ||
| 650 | 0 | |a Big data. | |
| 650 | 0 | |a Computer simulation. | |
| 650 | 0 | |a Engineering |x Data processing. | |
| 653 | |a Algorithms and techniques. | ||
| 653 | |a Anomaly detection. | ||
| 653 | |a Big data processing. | ||
| 653 | |a Cloud computing in data science. | ||
| 653 | |a Data privacy and security. | ||
| 653 | |a Data visualization. | ||
| 653 | |a Emerging trends and innovations. | ||
| 653 | |a Enabling reproducibility. | ||
| 653 | |a Ethical considerations and bias in data science. | ||
| 653 | |a Fundamental of data processing. | ||
| 653 | |a Industry applications. | ||
| 653 | |a Machine learning interpretability. | ||
| 653 | |a Modeling and evaluation. | ||
| 653 | |a Natural language processing (NLP) | ||
| 653 | |a Time series analysis. | ||
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| 700 | 1 | |a Sharma, Sachin |e editor. | |
| 700 | 1 | |a Sharma, Seema |c (Computer scientist) |e editor. | |
| 700 | 1 | |a Whig, Pawan |d 1980- |e editor. | |
| 700 | 1 | |a Yathiraju, Nikhitha |d 1994- |e editor. | |
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| contents | Chapter 1. Introduction to data processing: understanding the core concepts of data modeling -- Chapter 2. Machine learning mastery: practical insights for data processing -- Chapter 3. Algorithmic insights: exploring AI and ML in practical applications -- Chapter 4. Architecture, framework, and models for edge-AI in healthcare -- Chapter 5. AI-driven modeling: from concept to implementation -- Chapter 6. Agricultural insights: practical applications of data processing, algorithms, and modeling in farming -- Chapter 7. A novel online job scam detection of imbalanced data using ML and NLP models -- Chapter 8. Data analysis using IoT technologies for enhanced healthcare decision-making -- Chapter 9. Data privacy, compliance, and security including AI ML: healthcare -- Chapter 10. Data privacy, compliance, and security in cloud computing for finance -- Chapter 11. Demystifying machine learning by unraveling interpretability -- Chapter 12. Mastering data management: practical applications of data processing, algorithms, and modeling -- Chapter 13. Measuring psychometric analysis of stress level in learners across multiple parameters using machine learning -- Chapter 14. Navigating the essential fundamentals of data processing for modern enterprises -- Chapter 15. Optimizing with intelligence: harnessing AI and ML algorithms for real-world solutions -- Chapter 16. Smart data processing: unleashing the power of AI and ML -- Chapter 17. Unleashing the power of cloud computing for data science -- Chapter 18. Unveiling the frontiers: latest advancements in data science techniques and applications -- Chapter 19. Using complex network analysis techniques to uncover fraudulent activity in connected healthcare systems -- Chapter 20. Challenges and future directions in anomaly detection. |
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| dewey-ones | 620 - Engineering and allied operations |
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| dewey-search | 620.00285 |
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| dewey-tens | 620 - Engineering and allied operations |
| format | Electronic eBook |
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| isbn | 9798369329108 |
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| spelling | Practical applications of data processing, algorithms, and modeling Pawan Whig, Sachin Sharma, Seema Sharma, Anupriya Jain, Nikhitha Yathiraju. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global 2024. 27 PDFs (313 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Chapter 1. Introduction to data processing: understanding the core concepts of data modeling -- Chapter 2. Machine learning mastery: practical insights for data processing -- Chapter 3. Algorithmic insights: exploring AI and ML in practical applications -- Chapter 4. Architecture, framework, and models for edge-AI in healthcare -- Chapter 5. AI-driven modeling: from concept to implementation -- Chapter 6. Agricultural insights: practical applications of data processing, algorithms, and modeling in farming -- Chapter 7. A novel online job scam detection of imbalanced data using ML and NLP models -- Chapter 8. Data analysis using IoT technologies for enhanced healthcare decision-making -- Chapter 9. Data privacy, compliance, and security including AI ML: healthcare -- Chapter 10. Data privacy, compliance, and security in cloud computing for finance -- Chapter 11. Demystifying machine learning by unraveling interpretability -- Chapter 12. Mastering data management: practical applications of data processing, algorithms, and modeling -- Chapter 13. Measuring psychometric analysis of stress level in learners across multiple parameters using machine learning -- Chapter 14. Navigating the essential fundamentals of data processing for modern enterprises -- Chapter 15. Optimizing with intelligence: harnessing AI and ML algorithms for real-world solutions -- Chapter 16. Smart data processing: unleashing the power of AI and ML -- Chapter 17. Unleashing the power of cloud computing for data science -- Chapter 18. Unveiling the frontiers: latest advancements in data science techniques and applications -- Chapter 19. Using complex network analysis techniques to uncover fraudulent activity in connected healthcare systems -- Chapter 20. Challenges and future directions in anomaly detection. Restricted to subscribers or individual electronic text purchasers. "The book serves as a practical guide, providing hands-on examples, case studies, and problem-solving scenarios. It aims to empower readers to confidently navigate through data challenges and make informed decisions using data-driven insights"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 05/17/2024). Big data. Computer simulation. Engineering Data processing. Algorithms and techniques. Anomaly detection. Big data processing. Cloud computing in data science. Data privacy and security. Data visualization. Emerging trends and innovations. Enabling reproducibility. Ethical considerations and bias in data science. Fundamental of data processing. Industry applications. Machine learning interpretability. Modeling and evaluation. Natural language processing (NLP) Time series analysis. Electronic books. Jain, Anupriya 1977- editor. Sharma, Sachin editor. Sharma, Seema (Computer scientist) editor. Whig, Pawan 1980- editor. Yathiraju, Nikhitha 1994- editor. IGI Global, publisher. Print version: 9798369329092 |
| spellingShingle | Practical applications of data processing, algorithms, and modeling Chapter 1. Introduction to data processing: understanding the core concepts of data modeling -- Chapter 2. Machine learning mastery: practical insights for data processing -- Chapter 3. Algorithmic insights: exploring AI and ML in practical applications -- Chapter 4. Architecture, framework, and models for edge-AI in healthcare -- Chapter 5. AI-driven modeling: from concept to implementation -- Chapter 6. Agricultural insights: practical applications of data processing, algorithms, and modeling in farming -- Chapter 7. A novel online job scam detection of imbalanced data using ML and NLP models -- Chapter 8. Data analysis using IoT technologies for enhanced healthcare decision-making -- Chapter 9. Data privacy, compliance, and security including AI ML: healthcare -- Chapter 10. Data privacy, compliance, and security in cloud computing for finance -- Chapter 11. Demystifying machine learning by unraveling interpretability -- Chapter 12. Mastering data management: practical applications of data processing, algorithms, and modeling -- Chapter 13. Measuring psychometric analysis of stress level in learners across multiple parameters using machine learning -- Chapter 14. Navigating the essential fundamentals of data processing for modern enterprises -- Chapter 15. Optimizing with intelligence: harnessing AI and ML algorithms for real-world solutions -- Chapter 16. Smart data processing: unleashing the power of AI and ML -- Chapter 17. Unleashing the power of cloud computing for data science -- Chapter 18. Unveiling the frontiers: latest advancements in data science techniques and applications -- Chapter 19. Using complex network analysis techniques to uncover fraudulent activity in connected healthcare systems -- Chapter 20. Challenges and future directions in anomaly detection. Big data. Computer simulation. Engineering Data processing. |
| title | Practical applications of data processing, algorithms, and modeling |
| title_auth | Practical applications of data processing, algorithms, and modeling |
| title_exact_search | Practical applications of data processing, algorithms, and modeling |
| title_full | Practical applications of data processing, algorithms, and modeling Pawan Whig, Sachin Sharma, Seema Sharma, Anupriya Jain, Nikhitha Yathiraju. |
| title_fullStr | Practical applications of data processing, algorithms, and modeling Pawan Whig, Sachin Sharma, Seema Sharma, Anupriya Jain, Nikhitha Yathiraju. |
| title_full_unstemmed | Practical applications of data processing, algorithms, and modeling Pawan Whig, Sachin Sharma, Seema Sharma, Anupriya Jain, Nikhitha Yathiraju. |
| title_short | Practical applications of data processing, algorithms, and modeling |
| title_sort | practical applications of data processing algorithms and modeling |
| topic | Big data. Computer simulation. Engineering Data processing. |
| topic_facet | Big data. Computer simulation. Engineering Data processing. Electronic books. |
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