Assessing a Student’s Interest in College Using Machine Learning
Keywords:
College Interest, EnrollmentAbstract
We reviewed machine learning concepts and applied them to a data set of students to create a model that identifies students who may go to college. The data set originally had 1000 students. After the removal of the students who either have parents who are too old or too young, the data set shrunk to 992 students. One of the most widely used open-source libraries, Keras, which is within TensorFlow, is used in this analysis. We use Neural Networks with a sigmoid activation function in the output layer. The dataset is divided into a training dataset (75%) and a validation dataset (25%). The model is trained on the training set. The validation set shows the model generalizes well to new examples.
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