Data science and data analytics: opportunities and challenges
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Boca Raton
CRC Press
2022
|
| Ausgabe: | First edition |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xvii, 463 Seiten Illustrationen, Diagramme |
| ISBN: | 9780367628826 |
Internformat
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Datensatz im Suchindex
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| adam_text | Contents Preface...........................................................................................................................................................................ix Editors...........................................................................................................................................................................xi Contributors..............................................................................................................................................................xiii Section I Introduction about Data Science and Data Analytics 1. Data Science and Data Analytics: Artificial Intelligence and Machine Learning Integrated Based Approach............................................................................................................ 3 Šumika Chauhan, Manmohan Singh, and Ashwani Kumar Aggarwal 2. IoT Analytics/Data Science for IoT.............................................................................................. 19 T. Perarasi, R. Gayathri, M. Leeban Moses, and B. Vinoth 3. A Model to Identify Agriculture Production Using Data Science Techniques.................... 33 D. Anantha Reddy, Sanjay Kumar, and Rakesh Tripathi 4. Identification and Classification of Paddy Crop Diseases Using Big Data Machine Learning Techniques..................................................................................................... 47 Anisha P. Rodrigues, Joyston Menezes, Roshan Fernandes, Aishwarya, Niranjan N. Chiplunkar, and Vijaya Padmanabha Section II Algorithms, Methods, and Tools for Data
Science and Data Analytics 5. Crop Models and Decision Support Systems Using Machine Learning............................... 67 B. Vignesh and G. Suganya 6. An Ameliorated Methodology to Predict Diabetes Mellitus Using Random Forest................................................................................................................................................83 Arunakumari B. N., Aman Rai, and Shashidhar R. 7. High Dimensionality Dataset Reduction Methodologies in Applied Machine Learning............................................................................................................................................97 Farhan Hai Khan and Tannistha Pal 8. Hybrid Cellular Automata Models for Discrete Dynamical Systems....................................145 Sreeya Ghosh and Sumita Basu 9. An Efficient Imputation Strategy Based on Adaptive Filter for Large Missing Value Datasets.................................................................................................................161 S. Radhika, A. Chandrasekar, and Felix Albu 10. An Analysis of Derivative-Based Optimizers on Deep Neural Network Models...............173 Arma Pavate and Rajesh Bansode
VI Contents Section III Applications of Data Science and Data Analytics 11. Wheat Rust Disease Detection Using DeepLearning............................................................191 Sudhir Kumar Mohapatra, Srinivas Prasad, and Sarat Chandra Nayak 12. A Novel Data Analytics and Machine Learning Model towards Prediction and Classification of Chronic Obstructive Pulmonary Disease................................................. 203 Sridevi U. K., Sophia S., Boseliu Prabhu S.R., Zubair Baig, and P. Thamaraiselvi 13. A Novel Multimodal Risk Disease Prediction of Coronavirus by Using Hierarchical LSTM Methods...................................................................................................................... 217 V. Kakulapati, BasavaRaju Kachapuram, Appiah Prince, and P. Shiva Kalyan 14. A Tier-based Educational Analytics Framework.................................................................233 .laved Nazura and Paul Anand 15. Breast Invasive Ductal Carcinoma Classification Based on Deep Transfer Learning Models with Histopathology Images.....................................................................................249 Saikat Islam Khan, Pulak Kanti Bhowmicka, Nazrul Islama, Mostofa Kamal Nasıra, and Jia Uddin 16. Prediction of Acoustic Performance Using Machine Learning Techniques...................... 267 Ratnavel Rajalakshmi, S. Jeyanthi, Yuvaraj L., Pradeep M., Jeyakrishna S., and Abhishek Krishnaswami Section IV Issue and Challenges in Data Science and Data Analytics 17. Feedforward Multi-Layer Perceptron Training by Hybridized Method between
Genetic Algorithm and Artificial Bee Colony......................................................................279 Aleksa Cuk, Timea Bezdan, Nebojsa Bacanin, Miodrag Zivkovic, K. Venkatachalam, Tarik A. Rashid, and V. Kanchana Devi 18. Algorithmic Trading Using Trend Following Strategy: Evidence from Indian Information Technology Stocks............................................................................................ 293 Molla Ramizur Rahman 19. A Novel Data Science Approach for Business and Decision Making for Prediction of Stock Market Movement Using Twitter Data and News Sentiments............................305 S. Kumar Chandar, Hitesh Punjabi, Mahesh Kumar Sharda, and Jehan Murugadhas 20. Churn Prediction in Banking the Sector.............................................................................. 317 Shreyas Hingmire, Jawwad Khan, Ashutosh Pandey, and Arma Pavate 21. Machine and Deep Learning Techniques for Internet of Things Based Cloud Systems........................................................................................................................ 331 Raswitha Bandi and K. Tejaswini
Contents vil Section V Future Research Opportunities towards Data Science and Data Analytics 22. Dialect Identification of the Bengali Language........................................................................ 357 Elizabeth Behrman, Arijit Santra, Siladitya Sarkar, Prantik Roy, Ritika Yadav, Soumi Dutta, and Arijit Ghosal 23. Real-Time Security Using Computer Vision...........................................................................375 Bijoy Kumar Mandal and Niloy Sarkar 24. Data Analytics for Detecting DDoS Attacks in Network Traffic..........................................389 Ciza Thomas and Rejimol Robinson R.R. 25. Detection of Patterns in Attributed Graph Using Graph Mining........................................409 Bapuji Rao 26. Analysis and Prediction of the Update of Mobile Android Version................................... 433 Арата Mohan and R. Maheswari Index.......................................................................................................................................................453
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| adam_txt |
Contents Preface.ix Editors.xi Contributors.xiii Section I Introduction about Data Science and Data Analytics 1. Data Science and Data Analytics: Artificial Intelligence and Machine Learning Integrated Based Approach. 3 Šumika Chauhan, Manmohan Singh, and Ashwani Kumar Aggarwal 2. IoT Analytics/Data Science for IoT. 19 T. Perarasi, R. Gayathri, M. Leeban Moses, and B. Vinoth 3. A Model to Identify Agriculture Production Using Data Science Techniques. 33 D. Anantha Reddy, Sanjay Kumar, and Rakesh Tripathi 4. Identification and Classification of Paddy Crop Diseases Using Big Data Machine Learning Techniques. 47 Anisha P. Rodrigues, Joyston Menezes, Roshan Fernandes, Aishwarya, Niranjan N. Chiplunkar, and Vijaya Padmanabha Section II Algorithms, Methods, and Tools for Data
Science and Data Analytics 5. Crop Models and Decision Support Systems Using Machine Learning. 67 B. Vignesh and G. Suganya 6. An Ameliorated Methodology to Predict Diabetes Mellitus Using Random Forest.83 Arunakumari B. N., Aman Rai, and Shashidhar R. 7. High Dimensionality Dataset Reduction Methodologies in Applied Machine Learning.97 Farhan Hai Khan and Tannistha Pal 8. Hybrid Cellular Automata Models for Discrete Dynamical Systems.145 Sreeya Ghosh and Sumita Basu 9. An Efficient Imputation Strategy Based on Adaptive Filter for Large Missing Value Datasets.161 S. Radhika, A. Chandrasekar, and Felix Albu 10. An Analysis of Derivative-Based Optimizers on Deep Neural Network Models.173 Arma Pavate and Rajesh Bansode
VI Contents Section III Applications of Data Science and Data Analytics 11. Wheat Rust Disease Detection Using DeepLearning.191 Sudhir Kumar Mohapatra, Srinivas Prasad, and Sarat Chandra Nayak 12. A Novel Data Analytics and Machine Learning Model towards Prediction and Classification of Chronic Obstructive Pulmonary Disease. 203 Sridevi U. K., Sophia S., Boseliu Prabhu S.R., Zubair Baig, and P. Thamaraiselvi 13. A Novel Multimodal Risk Disease Prediction of Coronavirus by Using Hierarchical LSTM Methods. 217 V. Kakulapati, BasavaRaju Kachapuram, Appiah Prince, and P. Shiva Kalyan 14. A Tier-based Educational Analytics Framework.233 .laved Nazura and Paul Anand 15. Breast Invasive Ductal Carcinoma Classification Based on Deep Transfer Learning Models with Histopathology Images.249 Saikat Islam Khan, Pulak Kanti Bhowmicka, Nazrul Islama, Mostofa Kamal Nasıra, and Jia Uddin 16. Prediction of Acoustic Performance Using Machine Learning Techniques. 267 Ratnavel Rajalakshmi, S. Jeyanthi, Yuvaraj L., Pradeep M., Jeyakrishna S., and Abhishek Krishnaswami Section IV Issue and Challenges in Data Science and Data Analytics 17. Feedforward Multi-Layer Perceptron Training by Hybridized Method between
Genetic Algorithm and Artificial Bee Colony.279 Aleksa Cuk, Timea Bezdan, Nebojsa Bacanin, Miodrag Zivkovic, K. Venkatachalam, Tarik A. Rashid, and V. Kanchana Devi 18. Algorithmic Trading Using Trend Following Strategy: Evidence from Indian Information Technology Stocks. 293 Molla Ramizur Rahman 19. A Novel Data Science Approach for Business and Decision Making for Prediction of Stock Market Movement Using Twitter Data and News Sentiments.305 S. Kumar Chandar, Hitesh Punjabi, Mahesh Kumar Sharda, and Jehan Murugadhas 20. Churn Prediction in Banking the Sector. 317 Shreyas Hingmire, Jawwad Khan, Ashutosh Pandey, and Arma Pavate 21. Machine and Deep Learning Techniques for Internet of Things Based Cloud Systems. 331 Raswitha Bandi and K. Tejaswini
Contents vil Section V Future Research Opportunities towards Data Science and Data Analytics 22. Dialect Identification of the Bengali Language. 357 Elizabeth Behrman, Arijit Santra, Siladitya Sarkar, Prantik Roy, Ritika Yadav, Soumi Dutta, and Arijit Ghosal 23. Real-Time Security Using Computer Vision.375 Bijoy Kumar Mandal and Niloy Sarkar 24. Data Analytics for Detecting DDoS Attacks in Network Traffic.389 Ciza Thomas and Rejimol Robinson R.R. 25. Detection of Patterns in Attributed Graph Using Graph Mining.409 Bapuji Rao 26. Analysis and Prediction of the Update of Mobile Android Version. 433 Арата Mohan and R. Maheswari Index.453 |
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| spelling | Data science and data analytics opportunities and challenges edited by Amit Kumar Tyagi First edition Boca Raton CRC Press 2022 xvii, 463 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Data Science (DE-588)1140936166 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Data Science (DE-588)1140936166 s Maschinelles Lernen (DE-588)4193754-5 s DE-604 Tyagi, Amit Kumar 1988- Sonstige (DE-588)1231503025 oth Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=033042333&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Data science and data analytics opportunities and challenges |
| title_auth | Data science and data analytics opportunities and challenges |
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| title_exact_search_txtP | Data science and data analytics opportunities and challenges |
| title_full | Data science and data analytics opportunities and challenges edited by Amit Kumar Tyagi |
| title_fullStr | Data science and data analytics opportunities and challenges edited by Amit Kumar Tyagi |
| title_full_unstemmed | Data science and data analytics opportunities and challenges edited by Amit Kumar Tyagi |
| title_short | Data science and data analytics |
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| title_sub | opportunities and challenges |
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