Probability and Statistics for Machine Learning: A Textbook

Author:   Charu C. Aggarwal
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2024
ISBN:  

9783031532818


Pages:   522
Publication Date:   15 May 2024
Format:   Hardback
Availability:   Not yet available   Availability explained
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Probability and Statistics for Machine Learning: A Textbook


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Author:   Charu C. Aggarwal
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2024
ISBN:  

9783031532818


ISBN 10:   3031532813
Pages:   522
Publication Date:   15 May 2024
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

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Charu C. Aggarwal is a Distinguished Research Staff Member (DRSM) at the IBM T. J. Watson Research Center in Yorktown Heights, New York. He completed his undergraduate degree in Computer Science from the Indian Institute of Technology at Kanpur in 1993 and his Ph.D. in Operations Research from the Massachusetts Institute of Technology in 1996. He has published more than 400 papers in refereed conferences and journals, and has applied for or been granted more than 80 patents. He is author or editor of 20 books, including textbooks on linear algebra, machine learning, neural networks, and outlier analysis. Because of the commercial value of his patents, he has thrice been designated a Master Inventor at IBM. He has received several awards, including the EDBT Test-of-Time Award (2014), the ACM SIGKDD Innovation Award (2019), the IEEE ICDM Research Contributions Award (2015), and the IIT Kanpur Distinguished Alumnus Award (2023).He is also a recipient of the W. Wallace McDowell Award, the highest award given solely by the IEEE Computer Society across the field of computer science. He has served as an editor-in-chief of ACM Books and is currently serving as an editor-in-chief of the ACM Transactions on Knowledge Discovery from Data. He is a fellow of the SIAM, ACM, and the IEEE, for“contributions to knowledge discovery and data mining algorithms.”

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