For those of you who have a bad taste in your mouth from earlier run-ins with regexs, this will be more use case focused and I will do my best to explain the search patterns I used.
Today we are going to examine methods for calculating z-scores for our data in the database. We want to do this transformation because, when we carry out logistic regression we want to be able to compare the effects of the different factors on fire probability.
I was sent a link to a tweet regarding election night forecasting and of course the default questions was... could be run under PL/R inside Postgres. Like about everything else at Crunchy Data we believe all things are better with Postgres.
Learn how you can leverage Python and Pandas from directly inside PostgreSQL to build your own recommendation engine.
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