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Responsible data scienceselect proceedings of ICDSE 2021 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Responsible data scienceedited by Jimson Mathew ... [et al.].
其他題名:	select proceedings of ICDSE 2021 /
其他題名:	ICDSE 2021
其他作者:	Mathew, Jimson.
團體作者:
出版者:	Singapore :Springer Nature Singapore :2022.
面頁冊數:	viii, 221 p. :ill. (some color), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Quantitative researchCongresses.
電子資源:	https://doi.org/10.1007/978-981-19-4453-6
ISBN:	9789811944536$q(electronic bk.)

Responsible data scienceselect proceedings of ICDSE 2021 /
Responsible data scienceselect proceedings of ICDSE 2021 /[electronic resource] :ICDSE 2021edited by Jimson Mathew ... [et al.]. - Singapore :Springer Nature Singapore :2022. - viii, 221 p. :ill. (some color), digital ;24 cm. - Lecture notes in electrical engineering,v. 9401876-1119 ;. - Lecture notes in electrical engineering ;v.132..

End-to-end Hierarchical Approach for Emotion Detection in short texts -- Towards an Enhanced Understanding of Bias in Pre-trained Neural Language Models: A Survey with Special Emphasis on Affective Bias -- Exploring Rawlsian Fairness for K-Means Clustering -- Hybrid Explainable Educational Recommender using Self Attention and Knowledge Based Systems for E-Learning in MOOC Platforms -- An Improved Recommendation System with Aspect-Based Sentiment Analysis -- Exploring Biomarker Identification and Mortality Prediction of COVID-19 Patients using ML Algorithms -- COVID-19 cases prediction based on LSTM and SIR model using social media -- Joint Geometrical and Statistical Alignment using Triplet loss for Deep Domain Adaptation -- Virtual Try-On Using Style Transfer -- Attention Mechanism in Convolutional Recurrent Neural Network for Improving Recognition Accuracy in Printed Devanagari Text.

This book comprises select proceedings of the 7th International Conference on Data Science and Engineering (ICDSE 2021) The contents of this book focus on responsible data science. This book tries to integrate research across diverse topics related to data science, such as fairness, trust, ethics, confidentiality, transparency, and accuracy. The chapters in this book represent research from different perspectives that offer novel theoretical implications that span multiple disciplines. The book will serve as a reference resource for researchers and practitioners in academia and industry.

ISBN: 9789811944536$q(electronic bk.)

Standard No.: 10.1007/978-981-19-4453-6doiSubjects--Topical Terms:

575536
Quantitative research
--Congresses.

LC Class. No.: QA76.9.Q36

Dewey Class. No.: 001.422

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