COVID-19 Cases Outbreak Prediction using Supervise Learning Models

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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.

Autorentext

Dr. 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.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09786203863086
    • Genre Information Technology
    • Anzahl Seiten 68
    • Größe H220mm x B150mm
    • Jahr 2021
    • EAN 9786203863086
    • Format Kartonierter Einband
    • ISBN 978-620-3-86308-6
    • Veröffentlichung 02.07.2021
    • Titel COVID-19 Cases Outbreak Prediction using Supervise Learning Models
    • Autor Sheshang Degadwala , Brijesh Patel , Dhairya Vyas
    • Herausgeber LAP LAMBERT Academic Publishing
    • Sprache Englisch

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