Learning the Hard Way: Regression to the Mean

Posted on Thu 20 June 2024 in TDDA • Tagged with TDDA, reproducibility, errors, interpretation

I was at the tenth PyData London Conference last weekend, which was excellent, as always. One of the keynote speakers was Rebecca Bilbro who gave a rather brilliant (and cleverly titled) talk called Mistakes Were Made: Data Science 10 Years In.

The title is, of course, a reference to the …

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Name Styles

Posted on Mon 04 March 2024 in TDDA • Tagged with TDDA, names

This is just a bit of fun, but I've always been interested in the different kinds of names allowed, encouraged, and used in different areas of computing and data.

A few years ago, I tweeted some well-known naming styles and a collection of lesser-known naming styles. I was playing about …

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TOMLParams: TOML-based parameter files made better

Posted on Sun 16 July 2023 in TDDA • Tagged with TDDA, reproducibility

TOMLParams is a new open-source library that helps Python developers to externalize parameters in TOML files. This post will explain why storing parameters in non-code files is beneficial (including for reproducibility), why TOML was chosen, and some of the useful features of the library, which include structured sets of parameters …

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TDDA on the Coding for Thought Podcast

Posted on Tue 11 July 2023 in TDDA • Tagged with podcast, TDDA

I had the pleasure of discussing TDDA with Peter Schmidt on his Coding for Thought podcast.

I think it came out really well, so this might be a nice way for people to learn about the ideas and motivations for the ideas and the library, which Simon Brown, Sam Rhynas …

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Posted on Thu 24 October 2019 in TDDA • Tagged with tdda, python, installation

This post is a standing post that we plan to try to keep up to date, describing options for obtaining the open-source Python TDDA library that we maintain.

Using pip from PyPI

If you don't need source, and have Python installed, the easiest way to get the TDDA library is …

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