I'm moving the opposite direction: Altair -> Plotly. I find altair to be too "grammar of graphics" for its own good. And the vega backend makes it hard to hack around. Saving to pdf or high-quality also takes extra steps with additional dependencies.
Highly recommend playing Pentiment. Good mystery adventure set in the backdrop of medieval Bavaria. Large part of the story happens in a monastery (and the surrounding town).
I also see a use-case for reading long fiction books. Recently, I've been reading Stormlight Archives (Book 3) on and off and there are times when I want to remember why character X did Y or what that epigraph means, etc.
I'm looking at the Fediverse explorer and I'm curious how to interpret the embeddings (or the distances between points). What does it mean when two instances are near each other (e.g., sigmoid.social and mastodon-belgium.be)? Is it related to the number of follows?
> The gap between tree-based models and deep learning becomes narrower as the dataset size increases (here: 10k -> 50k).
I am curious if there is a sample threshold where it's worth exploring deep learning approaches to tabular data. I wonder if there are other considerations (e.g., inference speed, explainability, etc.).