stevenae
stevenae on Hacker News
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 derived first, then optimized. We would observe users (irl), read their logs, then generate experiments to improve the behavior as measured by logs, and return to see if the experiment improves irl experiences. There were not many of us and we are around :)
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-positive values, for the logarithm step.
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 known as "transfer learning".
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.
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 top-end mirrorless cameras I use today.
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.
Fellow R / Polars user here. How (in what applications) do you use DuckDB?
Posted by
stevenae on Sunday August 11, 2024 @06:01PM
from the npr.org dept.
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://www.linkedin.com/in/steven-ellis-4b140533/
Email: On LinkedIn
I am a data scientist and machine learning engineer with several years of experience across startups, corporations, and the federal government. I first learned to program as a child with Logo, then as a teenager with C++ and Java, settling now on Python after stints with R and Javascript.
Have dealt with this a couple of times. I see you're feeling some kind of reaction. I recommend talking it out with someone (professional therapist or otherwise). Often times a frustrating relationship has a clear path to amelioration, but it takes "seeing with fresh eyes".
I'm not disagreeing with that, just stating how they define the term.
I haven't seen this reported. Do you have a source?