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Add AzureML Quickstart Guides (#4772)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Ophélie Le Mentec 2023-09-07 01:15:18 +02:00 • committed by GitHub
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@ -17,6 +17,7 @@ Here's a compilation of in-depth guides to help you master different aspects of
* [K-Fold Cross Validation](kfold-cross-validation.md) 🚀 NEW: Learn how to improve model generalization using K-Fold cross-validation technique.
* [Hyperparameter Tuning](hyperparameter-tuning.md) 🚀 NEW: Discover how to optimize your YOLO models by fine-tuning hyperparameters using the Tuner class and genetic evolution algorithms.
* [Using YOLOv8 with SAHI for Sliced Inference](sahi-tiled-inference.md) 🚀 NEW: Comprehensive guide on leveraging SAHI's sliced inference capabilities with YOLOv8 for object detection in high-resolution images.
* [AzureML Quickstart](azureml-quickstart.md) 🚀 NEW: Get up and running with Ultralytics YOLO models on Microsoft's Azure Machine Learning platform. Learn how to train, deploy, and scale your object detection projects in the cloud.
## Contribute to Our Guides
@ -24,4 +25,4 @@ We welcome contributions from the community! If you've mastered a particular asp
To get started, please read our [Contributing Guide](https://docs.ultralytics.com/help/contributing) for guidelines on how to open up a Pull Request (PR) 🛠️. We look forward to your contributions!
Let's work together to make the Ultralytics YOLO ecosystem more robust and versatile 🙏!
Let's work together to make the Ultralytics YOLO ecosystem more robust and versatile 🙏!