Uncovering Pattern in Education Data Through Machine Learning
The main aim of machine learning is to extend accuracy, gain knowledge and maximize the performance of the machine on its task performed. Machine learning allows the system to be told new things from knowledge by making self-learning algorithms. In ML large problem is subdivided into several small tasks and at the end are combined to build a machine learning model. A sufficient amount of data can build a good model. Similarly, with the help of ML today every task has become very easy to perform with high accuracy. In this paper, we will see how machine learning has influenced education system in today’s scenario. When every knowledge sector is going online machine learning, has proved to be boon to our education system by providing highest accuracy in students’ performance, field of interest, as well as result prediction. Here, in this research the use of classification algorithms such as Decision Tree, Naïve Bayes Classifier, Random Forest and Logistic Regression will be learned. Whereas, Logistic Regression and Random Forest algorithms will be performed on the input data to transform specifically using Python Jupyter Notebook.
Keywords - Machine Learning Algorithms, Artificial Intelligence, Educational Data Mining.