- Anglický jazyk
COVID-19 Cases Outbreak Prediction using Supervise Learning Models
Autor: Sheshang Degadwala
Authorities all over the world are using COVID-19 episode expectation models to make informed decisions and maintain necessary control steps. AI (ML)-based deciding components have proven to be useful in predicting perioperative outcomes and improving the... Viac o knihe
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O knihe
Authorities all over the world are using COVID-19 episode expectation models to make informed decisions and maintain necessary control steps. AI (ML)-based deciding components have proven to be useful in predicting perioperative outcomes and improving the dynamic of possible operations. For a long time, machine learning models have been used in a variety of applications that required recognisable proof and the prioritisation of unfavourable factors for a risk. To cope with anticipating problems, a few expectation strategies are commonly used. Authorities all over the world are using COVID-19 episode expectation models to make informed decisions and maintain necessary controls. AI (ML)-based deciding components have shown their worth in predicting perioperative outcomes and improving the dynamic of future operations. For a long time, machine learning models have been used in a variety of applications that needed recognisable proof and prioritisation of unfavourable factors for a danger. To cope with expecting problems, a few expectation strategies are in use.
- Vydavateľstvo: LAP LAMBERT Academic Publishing
- Rok vydania: 2021
- Formát: Paperback
- Rozmer: 220 x 150 mm
- Jazyk: Anglický jazyk
- ISBN: 9786203863086