Articles by John Mount

New Introduction to the data_algebra

October 31, 2019 | John Mount

We’ve had really good progress in bringing the Python data_algebra to feature parity with R rquery. In fact we are able to reproduced the New Introduction to rquery article as a “New Introduction to the data_algebra” here. The idea is: you may have good reasons to want ... [...Read more...]

AI for Engineers

October 9, 2019 | John Mount

For the last year we (Nina Zumel, and myself: John Mount) have had the honor of teaching the AI200 portion of LinkedIn’s AI Academy. John Mount at the LinkedIn campus Nina Zumel designed most of the material, and John Mount has been delivering it and bringing her feedback. We’...
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vtreat Cross Validation

October 6, 2019 | John Mount

Nina Zumel finished new documentation on how vtreat‘s cross validation works, which I want to share here. vtreat is a system that makes data preparation for machine learning a “one-liner” (available in R or available in Python). We have a set of starting off points here. These documents describe ... [...Read more...]

How to Prepare Data

September 26, 2019 | John Mount

Real world data can present a number of challenges to data science workflows. Even properly structured data (each interesting measurement already landed in distinct columns), can present problems, such as missing values and high cardinality categorical variables. In this note we describe some great tools for working with such data. ... [...Read more...]

Preparing Data for Supervised Classification

September 24, 2019 | John Mount

Nina Zumel has been polishing up new vtreat for Python documentation and tutorials. They are coming out so good that I find to be fair to the R community I must start to back-port this new documentation to vtreat for R. vtreat is a package for systematically preparing data for ... [...Read more...]
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