Probability, Random Variables, and Data Analytics with Engineering Applications
Shankar, P. Mohana
- 出版商: Springer
- 出版日期: 2021-02-09
- 售價: $4,780
- 貴賓價: 9.5 折 $4,541
- 語言: 英文
- 頁數: 473
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3030562581
- ISBN-13: 9783030562588
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相關分類:
Data Science
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相關主題
商品描述
- Bridges the gap between conceptual topics and data analytics through appropriate examples and exercises;
- Features 100's of exercises comprising of traditional analytical ones and others based on data sets relevant to machine vision, machine learning and medical diagnostics;
- Intersperses analytical approaches with computational ones, providing two-level verifications of a majority of examples and exercises.
作者簡介
Dr. P. Mohana Shankar received his PhD from the Indian Institute of Technology, Delhi in Electrical Engineering in 1980. He joined Drexel in 1982 and since 2001, he has been the Allen Rothwarf Professor in the Department of Electrical and Computer Engineering at Drexel University. He is also an Adjunct Professor at Thomas Jefferson University in Philadelphia since 1998. He has held several positions at Drexel including Interim Department Head, Electrical Engineering; Director, Graduate Programs, College of Engineering, and Program Director, Telecommunications Engineering. He was the recipient of the 2005-2006 Christian R. and Mary F. Lindback Foundation Award for Distinguished Teaching and the 21018-2019 University Award for Pedagogy and Assessment. He developed several courses and laboratories in fiber optics, wireless communications, probability, etc. . He has taught numerous courses at both the graduate and undergraduate level. He has published several books, including two at Springer and published several papers in journals and conference proceedings in the areas of fiber sensors, wireless communications, ultrasonic imaging, ultrasonic nondestructive testing, ultrasonic contrast agents, ultrasonic tissue characterization and pedagogy. During the past few years, he has published extensively in pedagogy devoted to the use of computations tools in undergraduate engineering courses in differential equations, linear algebra, wireless, probability and data analytics.