Publications by John Mount
R Tip: How To Look Up Matrix Values Quickly
R is a powerful data science language because, like Matlab, numpy, and Pandas, it exposes vectorized operations. That is, a user can perform operations on hundreds (or even billions) of cells by merely specifying the operation on the column or vector of values. Of course, sometimes it takes a while to figure out how to do this. Please read for a...
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Discount on Manning Books, Including our own Practical Data Science with R 2nd Edition
We have a discount on Manning Books, including our own Practical Data Science with R 2nd Edition! Manning.com is offering FREE shipping with code SHIP35 for US residents only. Use this link to link to purchase http://www.manning.com/?a_aid=zm. And, Manning.com is offering 50% off all eBooks and 35% off all print books. Take advantage of this gre...
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Nina and John Speaking at Why R? Webinar Thursday, May 7, 2020
Nina Zumel and John Mount will be speaking on advanced data preparation for supervised machine learning at the Why R? Webinar Thursday, May 7, 2020. This is a 8pm in a GMT+2 timezone, which for us is 11AM Pacific Time. Hope to see you there! Related To leave a comment for the author, please follow the link and comment on their blog: R – Wi...
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Thank you “Why R?” for Being Awesome Hosts
Thank you very much Why R? for being awesome hosts. We are really pleased with how your virtual MeetUp went. For those who missed it here is a link. Related To leave a comment for the author, please follow the link and comment on their blog: R – Win-Vector Blog. R-bloggers.com offers daily e-mail updates about R news and tutorials about le...
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Thank you “Why R?” for Being Awesome Hosts
Thank you very much Why R? for being awesome hosts. We are really pleased with how your virtual MeetUp went. For those who missed it here is a link. Related To leave a comment for the author, please follow the link and comment on their blog: R – Win-Vector Blog. R-bloggers.com offers daily e-mail updates about R news and tutorials about le...
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Deal of the Day May 10: Half off Practical Data Science with R, Second Editio
Deal of the Day May 10: Half off Practical Data Science with R, Second Edition. Use code dotd051020au at https://bit.ly/2xLRPCk Related To leave a comment for the author, please follow the link and comment on their blog: R – Win-Vector Blog. R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many othe...
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General Data Science Means Cross-Language Tools, Training, and Documentation
Data science is often a case of brining the tools to the problems and data, instead of insisting on bringing the problems and data to the tools. To support cross-language data science we have been working on cross-language tools, documentation, and training. For example: vtreat data preparation package for supervised machine learning available b...
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Data engineering and data shaping in Practical Data Science with R 2nd Edition
A kind reader recently shared the following comment on the Practical Data Science with R 2nd Edition live-site. Thanks for the chapter on data frames and data.tables. It has helped me overcome an obstacle freeing me from a lot of warnings telling me my data table was not a real . It reduced the calculation time for a scenario in modelStudio from...
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Don’t Feel Guilty About Selecting Variables
We have an exciting new article to share: Don’t Feel Guilty About Selecting Variables. If you are at all interested in the probabilistic justification of important data science techniques, such as variable selection or pruning, this should be an informative and fun read. “Data Science” is often criticized with the common slur “if it has s...
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How to Read Sourav Chatterjee’s Basic XICOR Definition
Introduction Professor Sourav Chatterjee recently published a new coefficient of correlation called XICOR (refs: JASA, R package, Arxiv, Hacker News, and a Python package (different author)). The basic formula (in the tie-free case) is: Take X and Y as n-vectors of observations of random variable. Compute the ranks r(i) of the Y observations. So...
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