README.md

---
license: apache-2.0
pipeline_tag: tabular-regression
---

# 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](https://www.kaggle.com/datasets/student-performance).

## 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:
```python
from tensorflow.keras.models import load_model

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