Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3615
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBodke, Kalpana-
dc.contributor.authorAnsari, Haaid (17DCO64)-
dc.contributor.authorHarnerkar, Reema Salahuddin (16CO02)-
dc.date.accessioned2021-11-03T07:16:45Z-
dc.date.available2021-11-03T07:16:45Z-
dc.date.issued2020-05-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3615-
dc.description.abstractToday in the world of growing technology the domain of artificial intelligence is the pioneer. There are majority of the advancements and applications of Artificial Intelligence that we hear about refer to a category of algorithms known as Machine Learning. Self-learning algorithms use statistics to draw models from huge amounts of data. Machine learning is able to make very precise assumptions about what we do, about the next activity we might want to do. Our project will be using machine learning in order to facilitate working of an employee management system and will help the HR manager to analyse the performance and growth of individual employee. Our project will also find any unusual pattern in the performance of employees Our project will be using Deep learning in order to facilitate the employee attrition that will lead to reduce the employee turnover for the company, which is huge amount of cost for a big organisation. Organisations face huge costs from employee turnover. For a progress in organisation its important to know which of your employees are important to the organisation. Our project will be using h2o package and lime package to implement employee attrition. Keywords: Attrition,Machine Learning, Data Mining, Training set, Training Data, Automated System, pattern Recognition, Deep learning, Knowledge extraction, Data preprocessing, knowledge extraction,Web module,Artificial Intelligence.en_US
dc.language.isoenen_US
dc.publisherAIKTCen_US
dc.subjectProject Report - COen_US
dc.titleNex-Gen power ERMen_US
dc.typeOtheren_US
Appears in Collections:Computer Engineering - Project Reports

Files in This Item:
File Description SizeFormat 
17DCO64.pdfBlack Book1.73 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.