Python-bloggers

Nina Zumel had a really great article on how to prepare a nice Keras performance plot using R. I will use this example to show some of the advantages of cdata record transform specifications. The model performance data from Keras is in the following... [...Read more...]

This note is a simple data wrangling example worked using both the Python data_algebra package and the R cdata package. Both of these packages make data wrangling easy through he use of coordinatized data concepts (relying heavily on Codd’s “rule of access”). The advantages of data_algebra and cdata are: The user specifies their desired transform … Continue reading Advanced Data Reshaping in Python and R [...Read more...]

Win Vector LLC‘s Dr. Nina Zumel has just released some new vtreat documentation. vtreat is a an all-in one step data preparation system that helps defend your machine learning algorithms from: Missing values Large cardinality categorical variables Novel levels from categorical variables I hoped she could get the Python vtreat documentation up to parity with … Continue reading New Getting Started with vtreat Documentation [...Read more...]

This article introduces the data_algebra project: a data processing tool family available in R and Python. These tools are designed to transform data either in-memory or on remote databases. In particular we will discuss the Python implementation (also called data_algebra) and its relation to the mature R implementations (rquery and rqdatatable). Introduction Parts of the … Continue reading Introducing data_algebra [...Read more...]

I was working through Kyle Miller‘s excellent note: “Tail call recursion in Python”, and decided to experiment with variations of the techniques. The idea is: one may want to eliminate use of the Python language call-stack in the case of a “tail calls” (a function call where the result is not used by the calling … Continue reading Eliminating Tail Calls in Python Using Exceptions [...Read more...]

In my ongoing quest to track The Popularity of Data Science Software, I've just updated my analysis of the job market. To save you from reading the entire tome, I'm reproducing that section here. Continue reading → [...Read more...]

In my neverending quest to track The Popularity of Data Science Software, it’s time to update the section on Scholarly Articles. The rapid growth of R could not go on forever and, as you’ll see below, its use actually declined … Continue reading → [...Read more...]

Random forest is a type of machine learning algorithm in which the algorithm makes multiple decision trees that may use different features and subsample to making as many trees as you specify. The trees then vote to determine the class of an example. This approach helps to deal with the high variance that is a […] [...Read more...]

How to use Python code inside R [...Read more...]

Dockerizing Data Science: Introduction PreReqs: Docker, images, and containers Dockerizing data science packages have become more relevant these days mainly because you can isolate your data science projects without breaking anything. Dockerizing data science projects also make most of your projects portable and sharable and not worrying about installing right dependencies (you python fans know... Continue Reading → [...Read more...]