student-performance-model

Student Performance Prediction Model

Model Description

This model is trained to predict student performance based on various socio-economic and academic factors. It uses a regression approach to estimate the final grades of students.

Dataset

The model was trained using the Student Performance Predictions Dataset from Kaggle, which includes features such as:

• Study time
• Parent education level
• Previous grades
• Absences

You can find the dataset here.

Training

The model was trained using the following configuration:

• Library: TensorFlow/Keras
• Model Type: Regression
• Evaluation Metrics: Mean Absolute Error (MAE)

Results

The model's performance was evaluated using the validation loss (val_loss), which was calculated as the Mean Absolute Error (MAE). The model achieved a MAE of X on the validation dataset.

Metrics

The model was evaluated using Mean Absolute Error (MAE) on the validation set, achieving a MAE score of [your score here].

How to Use

You can load the model and use it for prediction as follows:

from tensorflow.keras.models import load_model

model = load_model("student_performance_model.h5")
# Use the model for prediction