Data Analytics, Computational Statistics, and Operations Research for Engineers

preview-18
  • Data Analytics, Computational Statistics, and Operations Research for Engineers Book Detail

  • Author : Debabrata Samanta
  • Release Date : 2022-03-24
  • Publisher : CRC Press
  • Genre : Computers
  • Pages : 275
  • ISBN 13 : 1000550427
  • File Size : 51,51 MB

Data Analytics, Computational Statistics, and Operations Research for Engineers by Debabrata Samanta PDF Summary

Book Description: With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

Disclaimer: www.yourbookbest.com does not own Data Analytics, Computational Statistics, and Operations Research for Engineers books pdf, neither created or scanned. We just provide the link that is already available on the internet, public domain and in Google Drive. If any way it violates the law or has any issues, then kindly mail us via contact us page to request the removal of the link.

Engineering Analytics

Engineering Analytics

File Size : 42,42 MB
Total View : 1566 Views
DOWNLOAD

Engineering analytics is becoming a necessary skill for every engineer. Areas such as Operations Research, Simulation, and Machine Learning can be totally trans