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Applications of Machine Learning
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Applications of Machine Learning
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Applications of Machine Learning/ edited by Prashant Johri, Jitendra Kumar Verma, Sudip Paul.
其他作者:
Paul, Sudip.
面頁冊數:
XXII, 394 p. 158 illus., 112 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Probability and Statistics in Computer Science. -
電子資源:
https://doi.org/10.1007/978-981-15-3357-0
ISBN:
9789811533570
Applications of Machine Learning
Applications of Machine Learning
[electronic resource] /edited by Prashant Johri, Jitendra Kumar Verma, Sudip Paul. - 1st ed. 2020. - XXII, 394 p. 158 illus., 112 illus. in color.online resource. - Algorithms for Intelligent Systems,2524-7565. - Algorithms for Intelligent Systems,.
Statistical Learning Process for the Reduction of Sample Collection Assuring a Desired Level of Confidence -- Sentiment Analysis on Google Play Store Data using Deep Learning -- Managing the Data Meaning in the Data Stream Processing: A Systematic Literature Mapping -- Tracking an Object using Traditional MS (Mean Shift) and CBWH MS (Mean Shift) Algorithm with Kalman Filter -- Transfer Learning and Domain Adaptation for Named Entity Recognition -- Knowledge Graph from Informal Text: Architecture, Components, Algorithms and Applications -- Neighborhood-based Collaborative Recommendations: An Introduction -- Classification of Arabic Texts Using Singular Value Decomposition and Fuzzy C-Means Algorithms -- Echo State Network Based Nonlinear Channel Equalization in Wireless Communication System -- Melody Extraction from Music: A Comprehensive Study -- Comparative Analysis of Combined Gas Turbine-Steam Turbine Power Cycle Performance by Using Entropy Generation and Statistical Methodology -- Data Mining - A Tool for Handling Huge Voluminous Data -- Improved Training Pattern in Back Propagation Neural Networks Using Holt-Winters' Seasonal Method and Gradient Boosting Model -- Ensemble of Multi-headed Machine Learning Architectures for Time-series Forecasting of Healthcare Expenditures -- Applying Soft Computing Approaches To Investigate Software Fault Proneness in Agile Software Development Environment.
This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.
ISBN: 9789811533570
Standard No.: 10.1007/978-981-15-3357-0doiSubjects--Topical Terms:
669886
Probability and Statistics in Computer Science.
LC Class. No.: TA329-348
Dewey Class. No.: 519
Applications of Machine Learning
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Statistical Learning Process for the Reduction of Sample Collection Assuring a Desired Level of Confidence -- Sentiment Analysis on Google Play Store Data using Deep Learning -- Managing the Data Meaning in the Data Stream Processing: A Systematic Literature Mapping -- Tracking an Object using Traditional MS (Mean Shift) and CBWH MS (Mean Shift) Algorithm with Kalman Filter -- Transfer Learning and Domain Adaptation for Named Entity Recognition -- Knowledge Graph from Informal Text: Architecture, Components, Algorithms and Applications -- Neighborhood-based Collaborative Recommendations: An Introduction -- Classification of Arabic Texts Using Singular Value Decomposition and Fuzzy C-Means Algorithms -- Echo State Network Based Nonlinear Channel Equalization in Wireless Communication System -- Melody Extraction from Music: A Comprehensive Study -- Comparative Analysis of Combined Gas Turbine-Steam Turbine Power Cycle Performance by Using Entropy Generation and Statistical Methodology -- Data Mining - A Tool for Handling Huge Voluminous Data -- Improved Training Pattern in Back Propagation Neural Networks Using Holt-Winters' Seasonal Method and Gradient Boosting Model -- Ensemble of Multi-headed Machine Learning Architectures for Time-series Forecasting of Healthcare Expenditures -- Applying Soft Computing Approaches To Investigate Software Fault Proneness in Agile Software Development Environment.
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