An in-depth Analysis of ML Algorithms Student Performance Forecasting

Abstract

In educational field machine learning has a crucial role for predicting a student's academic performance by his past Data analytics. It is the most challenging and experimental study issue. The student's educational status is crucial in determining whether they are admitted to higher education. The learning processes, as well as personal and societal factors, are all impacted by student achievement. Machine learning (ML) algorithms have been increasingly used to predict student performance based on a range of factors such as academic performance, attendance, and co-curriculum activities.  This article illustrates in-depth analysis of the existing information om machine learning algorithms for student performance forecasting by using supervised learning algorithms, whether it is favorable or negative. which is helpful for academic progress. For this we must collect the real-time data from different Institution any pre-processing those data, and implement ML algorithms for Performance prediction.