Update README.md

README.md

@@ -17,16 +17,12 @@ tags:
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 # Depth Estimation Using ResNet50 and XGBoost
+## Author
+ - **Vishal Adithya.A**
 
 ## Overview
 This project demonstrates a depth estimation XgBoost Regressor model that predicts the average depth of images provided using features extracted from a pre-trained ResNet50 model.The model was trained upon the **NYUv2 dataset** ([0jl/NYUv2](https://huggingface.co/datasets/0jl/NYUv2)). The trained model is saved as using Python's `pickle` library for easy deployment and reuse.
 
-## License
-This project is licensed under the Apache License 2.0.
-
-## Author
-**Vishal Adithya.A**
-
 ### Loading the Model
 The model is saved as `model.pkl` using `pickle`. You can load and use it as follows:
 
@@ -112,6 +108,10 @@ If you want to retrain the model, follow these steps:
    ```
 NOTE: This pipeline has just the base fundamental code more additional parameter tunings and preprocessing steps were being conducted during the training of the original model
 
+
+## License
+This project is licensed under the Apache License 2.0.
+
 ## Acknowledgments
 - Hugging Face for hosting the NYUv2 dataset.
 - NVIDIA RTX 4060 Ti for providing efficient GPU acceleration.