Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource ML Algorithms and Their Approach on COVID-19 Data Analysis Subject The topic of the resource classification; covid analysis; covid data visualization; Machine learning; regression; supervised learning; un-supervised learning Description An account of the resource This chapter begins with characterizing Supervised Learning and Unsupervised learning and investigates Machine Learning algorithms in every one of the sub domains of Regression, Classification, Clustering, and so forth. It also talks about the engineering of calculations like Linear Regression, Logistic Regression, K-Means, K Nearest Neighbors, Hierarchical, DB Scan, Decision Tree, Random Forest Regression, and Random Forest classifier. Utilization of every algorithm to investigate the dataset will be displayed by carrying out it on renowned dataset model, and output of each piece of code is displayed with their preview. This section likewise takes care of the issue of predicting the future number of COVID-19 cases and the precision behind each model or algorithm is shown and investigated utilizing different measurements dependent on situation or issue articulation, for example, either issue is on forecast or order. This chapter does not focus on the solution of COVID-19 data analysis or expectation, rather it will be followed and will task different models dependent on need with conclusive target being clear comprehension of the Machine Learning algorithms and its execution in Python. 2023 Scrivener Publishing LLC. Creator An entity primarily responsible for making the resource Ashok K.; Reddy P.A.; Kumar K.P. Source A related resource from which the described resource is derived Data Engineering and Data Science: Concepts and Applications, pp. 335-349. Publisher An entity responsible for making the resource available wiley Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1002/9781119841999.ch14" target="_blank" rel="noreferrer noopener">https://doi.org/10.1002/9781119841999.ch14</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174105993&amp;doi=10.1002%2F9781119841999.ch14&amp;partnerID=40&amp;md5=474ddaa51fcf6f604ec1d41c321c3799" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174105993&amp;doi=10.1002%2f9781119841999.ch14&amp;partnerID=40&amp;md5=474ddaa51fcf6f604ec1d41c321c3799</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-111984199-9; 978-111984187-6 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ashok K., Department of CS, Kyungpook National University, Daegu, South Korea; Reddy P.A., Department of CSE, Christ University, Karnataka, Bangalore, India; Kumar K.P., Department of CSE, Christ University, Karnataka, Bangalore, India