Skip to main content

Mathematical Methods in Data Science

  • 1st Edition - January 6, 2023
  • Authors: Jingli Ren, Haiyan Wang
  • Language: English
  • Paperback ISBN:
    9 7 8 - 0 - 4 4 3 - 1 8 6 7 9 - 0
  • eBook ISBN:
    9 7 8 - 0 - 4 4 3 - 1 8 6 8 0 - 6

Mathematical Methods in Data Science covers a broad range of mathematical tools used in data science, including calculus, linear algebra, optimization, network analysis, probabili… Read more

Mathematical Methods in Data Science

Purchase options

Limited Offer

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code is needed.

Book bundle cover eBook and print

Institutional subscription on ScienceDirect

Request a sales quote

Mathematical Methods in Data Science covers a broad range of mathematical tools used in data science, including calculus, linear algebra, optimization, network analysis, probability and differential equations. Based on the authors’ recently published and previously unpublished results, this book introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for data
analysis and prediction. With data science being used in virtually every aspect of our society, the book includes examples and problems arising in data science and the clear explanation of advanced mathematical concepts, especially data-driven differential equations, making it accessible to researchers and graduate students in mathematics and data science.