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Alumni Job Analysis & Success Rate Prediction by Machine Learning Techniques

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dc.contributor.author Mostakim, K. M.
dc.contributor.author Rahman, Anisur
dc.contributor.author Rahaman, Sohanur
dc.date.accessioned 2022-02-09T04:31:43Z
dc.date.available 2022-02-09T04:31:43Z
dc.date.issued 2021-06-01
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7016
dc.description.abstract Machine getting to know makes a specialty of the development of Computer packages which could get records and use it to discover on their own. This thesis centers on the job analysis of the Alumni. The job analysis helped out through a poll study follows. We want to build an “Alumni Job Analysis & Success Rate Prediction by Machine Learning Techniques”. Many people work at different farms or companies such as software firms, software companies. For the basis of Last Education, Programming Language, Monthly Salary and Company Rating. We can classify different types of classes such as Excellent, Very Good, Good, and Average. Our data is synthetic data. We collected our data from alumni. We have used Company rating from Google to make our dataset. At that point, machine learning classifications are applied to the dataset. Finally, a proficient model is created to predict a Success Rate. This model gives great classification measures with the dataset. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Computer program language en_US
dc.subject Machine learning en_US
dc.title Alumni Job Analysis & Success Rate Prediction by Machine Learning Techniques en_US
dc.type Other en_US


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