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 Conference Papers Conference Paper Faculty Publications- Conference Papers 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 A Machine Learning Approach for Revving Up Revenue of Indian Tech Companies Subject The topic of the resource arima; fb prophet; indian tech companies; machine learning; revenue; v.a.r model Description An account of the resource This study addresses a critical gap in research by examining the effectiveness of various machine learning models in predicting revenue for Indian tech companies. The V.A.R, ARIMA, simple moving average, weighted moving average, and FB Prophet models were employed and their performances was compared. The findings demonstrate that FB Prophet consistently outperforms other models, exhibiting superior accuracy in revenue forecasting. This underscores FB Prophet's potential to offer precise revenue predictions, enabling companies to gain insights into their financial health, anticipate market trends, and optimize decision-making. Future research could further enhance accuracy by incorporating economic indicators, providing a more holistic view of revenue dynamics and empowering companies to make more informed strategic decisions. 2024 IEEE. Creator An entity primarily responsible for making the resource Tungar S.K.; Umme Salma M. Source A related resource from which the described resource is derived 2nd IEEE International Conference on Data Science and Information System, ICDSIS 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICDSIS61070.2024.10594491" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICDSIS61070.2024.10594491</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200126947&amp;doi=10.1109%2FICDSIS61070.2024.10594491&amp;partnerID=40&amp;md5=839ff3e2b69f9adccb24eb4e56707556" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200126947&amp;doi=10.1109%2fICDSIS61070.2024.10594491&amp;partnerID=40&amp;md5=839ff3e2b69f9adccb24eb4e56707556</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038166-5 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Tungar S.K., Christ (Deemed To Be University), Department Of Statistics And Data Science, Karnataka, Bengaluru, India; Umme Salma M., Christ (Deemed To Be University), Department Of Statistics And Data Science, Karnataka, Bengaluru, India