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dc.contributor.authorPRABHAKAR-
dc.date.accessioned2022-06-30T07:36:47Z-
dc.date.available2022-06-30T07:36:47Z-
dc.date.issued2022-05-
dc.identifier.urihttp://dspace.dtu.ac.in:8080/jspui/handle/repository/19237-
dc.description.abstractMachine learning is used in several types of problems and performing very well in achieving solutions for those. Similarly, we are going to explore ways in which a software development company can increase their efficiency and enhance product quality by use of this. A company’s efficiency depends majorly upon the workforce and workflow they are using. Maintaining workforce quality and using an efficient workflow can help them in producing quality output. Voluntary Employee turnover is a great threat for all major companies across the globe as company’s overall performance is highly dependent on employee. A lot of investment is done by companies to firstly find a suitable employee and their training according to needs and after all this in retaining those trained and skilled employees in their companies. ML is used to solve the issue of customer churn prediction and to resolve that issue, this study aims to use the same method to predict voluntary employee attrition. And Software testing is one of the crucial steps in software development and as well as time and energy consuming phase. There are many automation tools like selenium which offers ease to testing phase in many ways but to a limited extent. Also, there are SFP or software fault prediction systems which uses machine learning models and helps in predicting faults’ (strength, weakness, opportunity, and threats) analysis is one the first studies we do before starting our research in any field as it clears many myths and doubt before starting and gives a clear view of topic.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesTD-5803;-
dc.subjectCUSTOMER PREDICTIONen_US
dc.subjectVOLUNTARY EMPLOYEEen_US
dc.subjectCOMPANY'S EFFICIENCYen_US
dc.subjectAI/MLen_US
dc.titleAPPLICATION OF AI/ML IN OMPROVING A COMPANY'S EFFICIENCYen_US
dc.typeThesisen_US
Appears in Collections:M.E./M.Tech. Computer Engineering

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