Viewing profile — stevenae

The quantitative ux research team at Google was created for exactly this problem: a service which became popular before the right metrics existed, meaning metrics need to be derive…

This helped me, coming from an ml background: https://randomrealizations.com/posts/xgboost-explained/

Others mentioned county data. If you can get that, you can build something like I did for DC -- https://colab.research.google.com/drive/1Kep_9j_PN_SxX85PYHE...

My reading of this situation is that MAPE would do the opposite. Means are skewed towards outliers.

Thanks for the reply! I am outside the forecasting sphere. RMSLE gives proportional error (so, scale-invariant) without MAPE's systematic under-prediction bias. It does require all…

To clarify, you'd prefer rmsle?

For this and sibling -- yes. Essentially, using the output of any model as an input to another model is transfer learning.

> Lately, I just steal embeddings from big models and slap a dumb classifier on top. Works better, runs faster, less drama. You may know this but many don't -- this is broadly know…

Thank you!

How accurate is his claim that Augustus became emperor through (my paraphrasing) democratic means and promises to fix real problems for Romans?

This still strikes me as escapism.

https://en.m.wikipedia.org/wiki/Energy-based_model

There was a saying at Google, I code for free, they pay me for XYZ (literally everything else).

I guess my quibble is with the percentage, then. A good, cheap, plentiful camera belies the idea that only the top 0.1% of cameras were good.

Disagree with the first piece about only using the top 0.1%. I grew up (through my 20's) shooting on a Pentax K1000, cheap workhorse of a camera, and I preferred its ergonomics to …

Location: Washington DC USA Remote: Hybrid or Remote Willing to relocate: NYC Technologies: r, python, sql Résumé/CV: https://www.linkedin.com/in/steven-ellis-4b140533 Data scienti…

Pro cameras do not do this to any degree. Edit: by default.

This is not true. R shines for classical stats and ML. If you are doing deep learning, you need Python.

From the guidelines [1]: Please don't sneer, including at the rest of the community. 1. https://news.ycombinator.com/newsguidelines.html

Save you some scrolling (link directly to comment): https://news.ycombinator.com/item?id=42119697

Fellow R / Polars user here. How (in what applications) do you use DuckDB?

Airplay? Lunadisplay?

Very much seems to be the case

Location: Washington, DC Remote: Yes, EST-PST Willing to relocate: Limited Technologies: Python/R, SQL, MapReduce, Causal Inference, Experimentation, Tabular ML Résumé/CV: https://…