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  Published Paper Details:

  Paper Title

PLACEMENT PREDICTION SYSTEM USING MACHINE LEARNING

  Authors

  Viram Vishnukant Rathi,  Mrs. Swati Sinha ,  Bhagyashree Gajanan Tayde,  Akshada Madhukar Shinde

  Keywords

Support Vector Machine Algorithm (SVM), Prediction..

  Abstract


Every student wants a perfect job and every student has their own dream company. But practically it is not possible for everyone to get into their dream company. The reason behind is that students lack knowledge regarding company placement criteria. To solve this issue this paper represents a placement prediction system with the help of Machine learning, in which we have used a support vector algorithm. We will generate one Google form which contains all students performance like there higher secondary marks diploma score communication skills, area of interest and most imp there dream job on that basis we will provide them necessary guidance to achieve their goal we will track there result each year , also their technical interest and will inform them how much efforts they need to take to achieve their dream job. Even if they miss their dream job due to company criteria our proposed algorithm will develop new data where we can suggest another alternation to students according to their achievements, their skills and also give guidelines at every phase.. Hence the future scope and relevance of the system will be discussed.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2004197

  Paper ID - 193454

  Page Number(s) - 1507-1515

  Pubished in - Volume 8 | Issue 4 | April 2020

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Viram Vishnukant Rathi,  Mrs. Swati Sinha ,  Bhagyashree Gajanan Tayde,  Akshada Madhukar Shinde,   "PLACEMENT PREDICTION SYSTEM USING MACHINE LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 4, pp.1507-1515, April 2020, Available at :http://www.ijcrt.org/papers/IJCRT2004197.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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