Minority report : can we predict emergencies / Data Science Salon.
"Forecasting is widely used in a number of business, but can it be used to optimize operations in an emergency department? This talk will walk through the development of a forecasting model to predict future arrivals to the emergency department. We will review the fundamentals of forecasting, d...
Saved in:
| Online Access: |
Streaming Video (via O'Reilly/Safari) |
|---|---|
| Other title: | Can we predict emergencies |
| Format: | Electronic Video |
| Language: | English |
| Published: |
[Austin, Texas] :
Data Science Salon,
2020.
|
| Subjects: |
MARC
| LEADER | 00000cgm a2200000 i 4500 | ||
|---|---|---|---|
| 001 | b11482931 | ||
| 006 | m o c | ||
| 007 | vz czazuu | ||
| 007 | cr ||||||||||| | ||
| 008 | 201104s2020 txu025 o o vleng d | ||
| 005 | 20240829142611.4 | ||
| 019 | |a 1436836050 | ||
| 035 | |a (OCoLC)safo1203113514 | ||
| 035 | |a (OCoLC)1203113514 |z (OCoLC)1436836050 | ||
| 037 | |a safo00000QPDJWYER7C | ||
| 040 | |a UMI |b eng |e rda |e pn |c UMI |d OCLCF |d OCLCO |d OCLCQ |d OCLCO |d OCLCL | ||
| 049 | |a GWRE | ||
| 050 | 4 | |a RA394 | |
| 245 | 0 | 0 | |a Minority report : |b can we predict emergencies / |c Data Science Salon. |
| 246 | 3 | 0 | |a Can we predict emergencies |
| 264 | 1 | |a [Austin, Texas] : |b Data Science Salon, |c 2020. | |
| 300 | |a 1 online resource (1 streaming video file (24 min., 14 sec.)) | ||
| 336 | |a two-dimensional moving image |b tdi |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 337 | |a video |b v |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 511 | 0 | |a Presenter, Michael Zelenetz. | |
| 500 | |a Title from resource description page (Safari, viewed November 3, 2020). | ||
| 500 | |a Place of publication from title screen. | ||
| 520 | |a "Forecasting is widely used in a number of business, but can it be used to optimize operations in an emergency department? This talk will walk through the development of a forecasting model to predict future arrivals to the emergency department. We will review the fundamentals of forecasting, discuss feature engineering, and how to get your first forecast off the ground."--Resource description page | ||
| 650 | 0 | |a Medical care |x Forecasting. | |
| 650 | 0 | |a Time-series analysis |x Mathematical models. | |
| 650 | 0 | |a Emergency medical services. | |
| 650 | 7 | |a Emergency medical services. |2 fast |0 (OCoLC)fst00908554 | |
| 650 | 7 | |a Medical care |x Forecasting. |2 fast |0 (OCoLC)fst01013810 | |
| 650 | 7 | |a Time-series analysis |x Mathematical models. |2 fast |0 (OCoLC)fst01151196 | |
| 700 | 1 | |a Zelenetz, Michael, |e on-screen presenter. | |
| 710 | 2 | |a Data Science Salon, |e publisher. | |
| 758 | |i has work: |a Minority Report (MovingImage) |1 https://id.oclc.org/worldcat/entity/E39PCYqfmBYqB3jWtJ7mgFXKV3 |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 856 | 4 | 0 | |u https://go.oreilly.com/UniOfColoradoBoulder/videos/~/00000QPDJWYER7C/?ar |z Streaming Video (via O'Reilly/Safari) |
| 915 | |a - | ||
| 956 | |a O'Reilly-Safari eBooks | ||
| 956 | |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 994 | |a 92 |b COD | ||
| 998 | |b Subsequent record output | ||
| 999 | f | f | |i d99084d2-d463-5d84-b5e8-06f0eef511ae |s aef7ff74-ee75-587c-a922-a68d4f8d60d5 |
| 952 | f | f | |p Can circulate |a University of Colorado Boulder |b Online |c Online |d Online |e RA394 |h Library of Congress classification |i web |n 1 |