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David Chudzicki about posts rss Stuff I've Made R Package for Average Predictive Comparisons Complicated models will often fit your data better than simple ones, but it's harder to understand what they're telling you. This is a project I'm working on to help with that.
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GPT4 can play chess
How general are Large Language Model (LLMs) chatbots? If you're interested in how AI will play out over the next few years, you might care how much "general" intelligence is embedded in these systems. Do they just predict text? Or can they learn to do oth
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Git First-Parent
Messy git history is a display problem, not a data problem. The first thing I encountered learning about git: there's a lot of conflict about whether it's important to keep a "clean" git history by squashing, rebasing instead of merging, etc. If the --fir
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Regexes for replacing ugly unittest-style assertions
In case they help anyone else, here are some regular expressions I used once to convert some ugly unittest-style assertions (e.g. self.assertEqual(something, something_else) to the pytest style (simply assert something == something_else ): sed -i ".bak" -
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An Interaction or Not? How a few ML Models Generalize to New Data
Source code for this post is here . This post examines how a few statistical and machine learning models respond to a simple toy example where they're asked to make predictions on new regions of feature space. The key question the models will answer diffe
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