Create README.md

README.md

@@ -0,0 +1,39 @@
+---
+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