It is a Python-based project that uses Bayes’ Theorem to predict whether a student is likely to pass an exam based on academic and behavioral factors such as:
Study hours
Attendance percentage
Previous exam performance
This project demonstrates how probabilistic reasoning can be applied to real-life educational predictions.
INPUT PARAMETERS
| Feature | Description |
|---|---|
| Study Hours | Daily study time (hours) |
| Attendance | Attendance percentage |
| Previous Score | Last exam marks |
| Exam Result | Pass / Fail |
Author Dinesh Pandiyan B
License This project is open-source and available under the MIT License.