Lecturer at UCLA Computer Science
Statistics Ph.D., UCLA
Machine learning, natural language processing, psychometrics, database systems.
Opinions my own.
(1) Large companies have been doing evaluation, on everything, for decades (it's all I did as a DS in Google Search). It was interesting seeing academia catch up, beyond accuracy/precision/recall/AUC/F1 etc. though they acted like this was a new concept.
(1) Large companies have been doing evaluation, on everything, for decades (it's all I did as a DS in Google Search). It was interesting seeing academia catch up, beyond accuracy/precision/recall/AUC/F1 etc. though they acted like this was a new concept.
(1) Evaluation of algorithms and solutions developed from LLM prompts and responses in systems is important (attention statisticians and data scientist). Log the results ("observability"). Iterate based on the results. 1/4
(1) Evaluation of algorithms and solutions developed from LLM prompts and responses in systems is important (attention statisticians and data scientist). Log the results ("observability"). Iterate based on the results. 1/4
(1) use for indexing where the keys follow a distribution: arxiv.org/abs/1712.01208
(2) use in evaluating cost of query plans
(3) probabilistic data structures
(1) use for indexing where the keys follow a distribution: arxiv.org/abs/1712.01208
(2) use in evaluating cost of query plans
(3) probabilistic data structures
Believe it or not, today was my first time ever using Tableau as a data scientist. And after today, it is also my last time.
Believe it or not, today was my first time ever using Tableau as a data scientist. And after today, it is also my last time.
x = 16 (sin x)^3
y = 13 cos x - 5 cos 2x - 2 cos 3x - cos 4x
x = 16 (sin x)^3
y = 13 cos x - 5 cos 2x - 2 cos 3x - cos 4x
www.cnbc.com/2025/01/18/p...
www.cnbc.com/2025/01/18/p...