COVID-19 Cases Outbreak Prediction using Supervise Learning Models
(Sprache: Englisch)
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...
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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.
Autoren-Porträt von Sheshang Degadwala, Brijesh Patel, Dhairya Vyas
Degadwala, SheshangDr. Sheshang D. Degadwala is presently working as Associate Professor and Head of Computer Engineering Department, Sigma Institute of Engineering, Vadodara. He has published 145 research paper in field of image processing and computer vision.he has published 10 books and 1 Indian Patent. He is microsoft certified in python and excel.
Bibliographische Angaben
- Autoren: Sheshang Degadwala , Brijesh Patel , Dhairya Vyas
- 2021, 68 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6203863084
- ISBN-13: 9786203863086
Sprache:
Englisch
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