Data Science and Its Applications
Material type:
TextPublication details: New York CRC Press 2024Description: xix, 358p. 24 x 18 cmISBN: - 9781032530765
- 006.3 SHA
| Item type | Current library | Collection | Call number | Status | Date due | Barcode |
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Reference
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Raj Kumar Goel Institute of Technology | IOT (Internet of Things) | 006.3 SHA (Browse shelf(Opens below)) | Not for loan | 96393 | |
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Reference
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Raj Kumar Goel Institute of Technology | IOT (Internet of Things) | 006.3 SHA (Browse shelf(Opens below)) | Not for loan | 96394 |
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| 006.3 PAD Artificial Intelligence | 006.3 PAD Artificial Intelligence | 006.3 SHA Data Science and Its Applications | 006.3 SHA Data Science and Its Applications | 006.31 BHA Machine Learning for Beginners | 006.31 BHA Machine Learning for Beginners | 006.31 GOP Applied Machine Learning |
Contents:
1. Introduction to Data Science: Review, Challenges and Opportunities
2. Recommender Systems: Challenges and Opportunities in the Age of Big Data and Artificial Intelligence
3. Machine Learning for Data Science Applications
4. Classification and Detection of Citrus Diseases using Deep Learning
5. Credibility Assessment of Healthcare Related Social Media Data
6. Filtering and Spectral Analysis of Time Series Data: A Signal Processing Perspective and Illustrative Application to Stock Market Index Movement Forecasting
7. Data Science in Education
8. Spectral characteristics and behavioral analysis of deep brain stimulation by the nature-inspired algorithm
9. Visual Question Answering system using integrated models of image captioning and BERT
10. Deep Neural Networks for Recommender Systems
11. Application of Data Science in Supply Chain Management: Real-world Case Study in Logistics
12. A Case Study on Disease Diagnosis using Gene Expression Data Classification with Feature Selection: Application of Data Science Techniques in Healthcare
13. Case Studies in Data Optimization using Python
14. Deep Parallel-Embedded BioNER Model for Biomedical Entity Extraction
15. Predict the Crime Rate against Women using Machine Learning Classification Techniques
16. Page Rank Based Extractive Text Summarization
17. Scene Text Analysis
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