Student Placement Aanalyzer:A Recommendation System Using Machine Learning

Information Science and Engineering

The Institutions today face a challenge of placements and to improve the same. It is a very complicated process to predict the placement of students manually. Educational institutions today strive to improvise the procedures and strategies that support decision making capabilities that improvise the students’ placements. This can be addressed by making use of machine learning technique to predict the placement of the students. We make use of the historical data of the past students, this data is considered as the training data set and is used to train the model. The system then predicts the placement status of the student to one of the five categories or statuses, viz., Dream Company, Core Company, Mass Recruiters, Not Eligible and Not Interested in Placements. This model helps the placement cell of the organization to identify the weaker students and provide extra care towards them so that they improve their performance henceforth. Furthermore, the students in the final as well as pre-final years of B. E or B. Tech course can also make use of this system to know their placement status that they are likely to achieve. By this knowledge they can put in the necessary efforts to achieve their goals and to get placed in better companies. Keyword: - Decision Tree Classifier, Sci-kit Learn, Machine Learning, Prediction, Logistic Regression

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