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 Stacked LSTM a Deep Learning model to predict Stock market Subject The topic of the resource Deep Learning; Machine Learning; RMSE; SLSTM; Stock market prediction; Stock markets Description An account of the resource The goal of Stock Market Prediction is to forecast the future value of a company's financial stocks. The use of machine learning and deep learning technologies in stock market prediction technologies is a recent trend. Machine learning makes predictions based on the values of current stock market indices by training on their previous values in sequential timely order using the artificial neural network, while deep learning makes predictions based on the values of current stock market indices by training on their previous values in sequential timely order using the artificial neural network. 2022 IEEE. Creator An entity primarily responsible for making the resource Jaswanth B.; Kaushik J. Source A related resource from which the described resource is derived Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022, pp. 17-22. 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 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICAC3N56670.2022.10074222" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICAC3N56670.2022.10074222</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152195442&amp;doi=10.1109%2FICAC3N56670.2022.10074222&amp;partnerID=40&amp;md5=13319ec412f5bdbf1abe917543ac6590" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152195442&amp;doi=10.1109%2fICAC3N56670.2022.10074222&amp;partnerID=40&amp;md5=13319ec412f5bdbf1abe917543ac6590</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166547436-8 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 Jaswanth B., Christ University, Department of Data Science, India; Kaushik J., Christ University, Department of Data Science, India, Mit (ADT) University, Pune, India