Why not WASM? Seems like something like duckdb-wasm or datafusion-wasm can do the same thing?
That's a lot of names for a bunch of tools that do a single task each.
What I would really benefit of is a hypothetical LLM chat app that is focused on data migration or processing pipelines.
It's super interesting to be able to see the data in the web
The iceberg reader sounds cool but how does it handle auth? Most iceberg tables are not publicly accessible.
Very cool stuff. Is this some kind of lighter weight duckdb-wasm? did I get this right?
Very cool, does `npx hyperparam dataset.parquet` phone home?
very nice. I wanted something like this for Parquet but couldn't find one, this one looks great.
Anyone benchmark this vs. duckdb-wasm?
You’re right. Pythons the worst
Looks interesting!
Though these tools might be interesting, I wish they had called this something else. This isn't at all related to the concept of hyperparameters which people commonly refer to as hyperparams. And in their copy, the only reference to hyperparameters seems to be misusing the term.
> This stems from an industry-wide realization that model performance is ultimately bounded by data quality, not just model architecture or hyperparameters.
Generally we think of model architecture + weights (parameters) as making up the model itself, and hyperparam(s|eters) are the more relevant to how one arrives at those weights -- and for this reason are more relevant to the efficacy of training than the performance of the resultant model.