Predicting Absenteeism of Students Using Deep Learning

• Tech Stack: Python, Scikit-learn, Numpy, Pandas
• Publication URL: Project Link

Developed and implemented deep learning models to analyze and predict student absenteeism, leveraging trial and error methodologies to optimize loss functions and enhance model accuracy. Demonstrated proficiency in using advanced data analytics and machine learning techniques to address real-world educational challenges.

Achieved significant improvements in prediction accuracy over traditional methods by innovating modifications in loss functions and optimizers. Successfully presented findings in comprehensive reports, including precision values, ROC curves, and PR curves, substantiating the effectiveness of deep learning approaches in educational data analytics.