Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Browse by topic Browse by titles Authors Reviewers Browse by issue Browse Help
Search
  Browse All Reviews > Mathematics Of Computing (G) > Probability And Statistics (G.3) > Statistical Computing (G.3...)  
 
Options:
 
  1-10 of 174 Reviews about "Statistical Computing (G.3...)": Date Reviewed
  Machine learning using R
Ramasubramanian K., Singh A.,  Apress, New York, NY, 2016. 566 pp. Type: Book (978-1-484223-33-8)

Karthik Ramasubramanian and Abhishek Singh, experts in data science and business analytics, have written a comprehensive reference book on machine learning using R. This book covers a relevant and hot topic in today’s digital world....

Oct 26 2017
  Introduction to the new statistics: estimation, open science, and beyond
Cumming G., Calin-Jageman R.,  Routledge, New York, NY, 2016. 594 pp. Type: Book (978-1-138825-52-9)

Statistics has many varied uses in society. This introductory statistics book would be of interest to undergraduate statistics students, university lecturers, and researchers. The book examines the use of statistics with regard to developing resea...

Aug 31 2017
  Financial analytics with R: building a laptop laboratory for data science
Bennett M., Hugen D.,  Cambridge University Press, New York, NY, 2016. 392 pp. Type: Book (978-1-107150-75-1)

Billed as “a training resource for ... students and professionals,” this title is a sophisticated manual on financial data manipulation, statistics, and R programming. It is by no means for the beginner or the faint of heart--a de...

Jun 23 2017
  ggplot2: elegant graphics for data analysis (2nd ed.)
Wickham H.,  Springer International Publishing, New York, NY, 2016. 260 pp. Type: Book (978-3-319242-75-0)

R is an open-source programming language that is popular for statistical computing and graphics. It provides a variety of statistical (linear and nonlinear modeling, statistical tests, time-series analysis, clustering, and so on) and graphical tec...

May 30 2017
  Introduction to statistical machine learning
Sugiyama M.,  Morgan Kaufmann Publishers Inc., San Francisco, CA, 2016. 534 pp. Type: Book, Reviews: (2 of 2)

The huge amount of data resulting from the increase in connected computers, mobile devices, and sensors in diverse domains has facilitated a boom of machine learning in recent years. Machine learning, the topic of this book, plays a central role i...

Apr 11 2017
  Interview questions in business analytics
Gupta B.,  Apress, New York, NY, 2016. 94 pp. Type: Book (978-1-484206-00-3)

Business analytics emphasizes date-driven, often statistical, business decision making. Graduates and job seekers interviewing for such employment, as well as interviewers, will find this list of approximately 200 subject matter questions, written...

Jan 31 2017
   Computer age statistical inference: algorithms, evidence, and data science
Efron B., Hastie T.,  Cambridge University Press, New York, NY, 2016. 476 pp. Type: Book (978-1-107149-89-2)

No healthy scientific discipline stands still, and active practitioners recognize the flux of ideas and frequently contribute to it. But the exigencies of pedagogy make it difficult for a student to understand the trajectory of a field. Textbooks ...

Jan 18 2017
   Introduction to statistical machine learning
Sugiyama M.,  Morgan Kaufmann Publishers Inc., San Francisco, CA, 2016. 534 pp. Type: Book, Reviews: (1 of 2)

Recently, I found myself giving an impromptu book review to someone in the bookshop near to my office. I noticed that a man was browsing through a book on machine learning that I had purchased a few months ago. I won’t mention the name of th...

Jan 11 2017
  Quadratic maps are hard to sample
Viola E.  ACM Transactions on Computation Theory 8(4): 1-4, 2016. Type: Article

A quadratic map is a function of the form f (x) = ax2 + bx + c, or more generally,...

Jul 26 2016
  Python for probability, statistics, and machine learning
Unpingco J.,  Springer International Publishing, New York, NY, 2016. 276 pp. Type: Book (978-3-319307-15-2)

Many recent books cover a combination of Python, data science, statistics, and machine learning. They vary widely in prerequisites and approach. This book does not include data science in its title and does not use large data sets. Its examples ar...

Jul 8 2016
 
 
 
Display per page
Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright © 2000-2017 ThinkLoud, Inc.
Terms of Use
| Privacy Policy