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I'm super excited to announce the release of glum (https://github.com/Quantco/glum/), a Python-first generalized linear modeling library. We focused a lot on correctness, performance and a powerful range of features. glum gets a 3-10x (or more) speed up over glmnet. It's also fun to use!
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We're also releasing tabmat (https://github.com/Quantco/tabmat/), a tabular matrix backend for glum. It supports mixes of dense, sparse and categorical matrices. On some operations, tabmat is 50x faster than scipy.sparse! And it's memory-efficient.
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GLMs are nice and all, but I'd also like to see some love for GAMs. pygam looks pretty much dead for some years now.