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Handbook of research on emerging tre...
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Solanki, Arun, (1985-)
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Handbook of research on emerging trends and applications of machine learning
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Handbook of research on emerging trends and applications of machine learning/ Arun Solanki, Sandeep Kumar, and Anand Nayyar, editors.
其他作者:
Solanki, Arun,
出版者:
Hershey, Pennsylvania :IGI Global, : 2020.,
面頁冊數:
1 online resource (xxxvi, 674 p.)
內容註:
Chapter 1. Method to rank academic institutes by the sentiment analysis of their online reviews -- Chapter 2. Machine learning in higher education: predicting student attrition status using educational data mining -- Chapter 3. Machine learning optimization techniques for 3D IC physical design -- Chapter 4. A novel approach to kinect-based gesture recognition for HCI applications -- Chapter 5. A survey on precision treatment for humans using cognitive machine learning techniques -- Chapter 6. Text classification using self-structure extended multinomial naive bayes -- Chapter 7. Applications of machine learning for software management -- Chapter 8. Creating paraphrase identification corpus for Indian languages: opensource data set for paraphrase creation -- Chapter 9. Deep learning approaches for textual sentiment analysis -- Chapter 10. Deep learning for next-generation inventive wireless networks: issues, challenges, and futuredirections -- Chapter 11. Demystifying disease identification and diagnosis using machine learning classification algorithms: demystify medical data with machine learning algorithms -- Chapter 12. Evolution of data analytics in healthcare -- Chapter 13. Implementation of machine learning in network security -- Chapter 14.Information retrieval in conjunction with deep learning -- Chapter 15. Interactive game-based motor rehabilitation using hybrid sensor architecture -- Chapter 17. Machine learning in 5G multimedia communications: open research challenges and applications -- Chapter 18. Machine learning in text analysis -- Chapter 19. Machine learning in the medical industry -- Chapter 20. Machine learning in video games -- Chapter 21. Multi-layer hybrid credit scoring model based on feature selection, ensemble learning, and ensemble classifier -- Chapter 22. Overview of machine learners in classifying of speech signals -- Chapter 23. Self-driving cars: role of machine learning -- Chapter 24. Sentiment analysis on social media: recent trends in machine learning -- Chapter 25. Social big data mining: a survey focused on sentiment analysis -- Chapter 26. Tool condition monitoring using artificial neural network models -- Chapter 27. Computer vision-based assistive technology for helping visually impaired and blind people using deep learning framework.
標題:
Machine learning. -
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-9643-1
ISBN:
9781522596455 (ebk.)
Handbook of research on emerging trends and applications of machine learning
Handbook of research on emerging trends and applications of machine learning
[electronic resource] /Arun Solanki, Sandeep Kumar, and Anand Nayyar, editors. - Hershey, Pennsylvania :IGI Global,2020. - 1 online resource (xxxvi, 674 p.)
Includes bibliographical references and index.
Chapter 1. Method to rank academic institutes by the sentiment analysis of their online reviews -- Chapter 2. Machine learning in higher education: predicting student attrition status using educational data mining -- Chapter 3. Machine learning optimization techniques for 3D IC physical design -- Chapter 4. A novel approach to kinect-based gesture recognition for HCI applications -- Chapter 5. A survey on precision treatment for humans using cognitive machine learning techniques -- Chapter 6. Text classification using self-structure extended multinomial naive bayes -- Chapter 7. Applications of machine learning for software management -- Chapter 8. Creating paraphrase identification corpus for Indian languages: opensource data set for paraphrase creation -- Chapter 9. Deep learning approaches for textual sentiment analysis -- Chapter 10. Deep learning for next-generation inventive wireless networks: issues, challenges, and futuredirections -- Chapter 11. Demystifying disease identification and diagnosis using machine learning classification algorithms: demystify medical data with machine learning algorithms -- Chapter 12. Evolution of data analytics in healthcare -- Chapter 13. Implementation of machine learning in network security -- Chapter 14.Information retrieval in conjunction with deep learning -- Chapter 15. Interactive game-based motor rehabilitation using hybrid sensor architecture -- Chapter 17. Machine learning in 5G multimedia communications: open research challenges and applications -- Chapter 18. Machine learning in text analysis -- Chapter 19. Machine learning in the medical industry -- Chapter 20. Machine learning in video games -- Chapter 21. Multi-layer hybrid credit scoring model based on feature selection, ensemble learning, and ensemble classifier -- Chapter 22. Overview of machine learners in classifying of speech signals -- Chapter 23. Self-driving cars: role of machine learning -- Chapter 24. Sentiment analysis on social media: recent trends in machine learning -- Chapter 25. Social big data mining: a survey focused on sentiment analysis -- Chapter 26. Tool condition monitoring using artificial neural network models -- Chapter 27. Computer vision-based assistive technology for helping visually impaired and blind people using deep learning framework.
"This book examines the role of machine learning in various applications such as data mining, natural language processing, image recognition, and expert systems"--
ISBN: 9781522596455 (ebk.)Subjects--Topical Terms:
533906
Machine learning.
LC Class. No.: Q325.5 / .H357 2020e
Dewey Class. No.: 006.3/1
Handbook of research on emerging trends and applications of machine learning
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Chapter 1. Method to rank academic institutes by the sentiment analysis of their online reviews -- Chapter 2. Machine learning in higher education: predicting student attrition status using educational data mining -- Chapter 3. Machine learning optimization techniques for 3D IC physical design -- Chapter 4. A novel approach to kinect-based gesture recognition for HCI applications -- Chapter 5. A survey on precision treatment for humans using cognitive machine learning techniques -- Chapter 6. Text classification using self-structure extended multinomial naive bayes -- Chapter 7. Applications of machine learning for software management -- Chapter 8. Creating paraphrase identification corpus for Indian languages: opensource data set for paraphrase creation -- Chapter 9. Deep learning approaches for textual sentiment analysis -- Chapter 10. Deep learning for next-generation inventive wireless networks: issues, challenges, and futuredirections -- Chapter 11. Demystifying disease identification and diagnosis using machine learning classification algorithms: demystify medical data with machine learning algorithms -- Chapter 12. Evolution of data analytics in healthcare -- Chapter 13. Implementation of machine learning in network security -- Chapter 14.Information retrieval in conjunction with deep learning -- Chapter 15. Interactive game-based motor rehabilitation using hybrid sensor architecture -- Chapter 17. Machine learning in 5G multimedia communications: open research challenges and applications -- Chapter 18. Machine learning in text analysis -- Chapter 19. Machine learning in the medical industry -- Chapter 20. Machine learning in video games -- Chapter 21. Multi-layer hybrid credit scoring model based on feature selection, ensemble learning, and ensemble classifier -- Chapter 22. Overview of machine learners in classifying of speech signals -- Chapter 23. Self-driving cars: role of machine learning -- Chapter 24. Sentiment analysis on social media: recent trends in machine learning -- Chapter 25. Social big data mining: a survey focused on sentiment analysis -- Chapter 26. Tool condition monitoring using artificial neural network models -- Chapter 27. Computer vision-based assistive technology for helping visually impaired and blind people using deep learning framework.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-9643-1
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