Update README.md

README.md

@@ -128,6 +128,27 @@ rmse = mean_squared_error(y_test, preds, squared=False)
 print(f"RMSE: {rmse}")
 ```
 
+
+---
+
+## Example Notebooks
+### 🚀 Interactive Baseline: XGBoost for Resource Estimation
+
+We provide a sample baseline implementation using **XGBoost** to demonstrate how to perform resource estimation (e.g., predicting `fit_time`) using the dataset's metadata.
+
+You can interactively explore and run this notebook on Google Colab:
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://huggingface.co/datasets/ICICLE-AI/ResourceEstimation_HLOGenCNN/blob/main/Baseline_XGBoost_Resource_Estimation.ipynb)
+**Baseline_XGBoost_Resource_Estimation.ipynb**
+
+This notebook covers:
+- Loading and preprocessing metadata from `dataset-new.csv`
+- Training an XGBoost regressor to predict training time
+- Evaluating model performance (e.g., RMSE)
+- Guidance for extending to advanced models (e.g., incorporating HLO graph features)
+
+> ⚡ **Note:** Make sure to adjust paths if cloning the dataset locally or integrating with Hugging Face `datasets` API.
+
 ---
 
 ### Loading HLO Graph Features