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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -23,7 +23,7 @@ batch scoring, realtime scoring, model training, MLOps, Azure Machine Learning,
2. [AI100 - Samples](#ai100)
3. [AI200 - Reference Architectures](#ai200)
4. [AI300 - Best Practices](#ai300)
6. [Contributing](#Contributing)
5. [Contributing](#Contributing)

# Getting Started <a name="Getting-Started"></a>
This repository is arranged as submodules so you can either pull all the tutorials or simply the ones you want.
Expand Down Expand Up @@ -70,7 +70,7 @@ Our reference architectures are arranged by scenario. Each architecture includes
| [Deploy R ML Model on Kubernetes](https://github.com/Azure/RealtimeRDeployment) | R | CPU | Real-Time Scoring | Deploy ML model for _real-time_ scoring on Kubernetes | |
| [Deploy R ML Model on Batch](https://github.com/Azure/RBatchScoring) | R | CPU | Scoring | Deploy forecasting model for _batch_ scoring using Azure Batch and doAzureParallel | |
| [Deploy Spark ML Model on Databricks](https://github.com/Azure/BatchSparkScoringPredictiveMaintenance) | Python | Spark | Batch Scoring | Deploy a classification model for _batch_ scoring using Databricks | |
| [Train Distributed Deep Leaning Model](https://github.com/Azure/DistributedDeepLearning/) | Python | GPU | Training | Distributed training of ResNet50 model using Batch AI | |
| [Train Distributed Deep Learning Model](https://github.com/Azure/DistributedDeepLearning/) | Python | GPU | Training | Distributed training of ResNet50 model using Batch AI | |

# AI300 - Best Practices <a name="ai300"></a>
Our best practices are arranged by topic. Each best practice repository includes open source methods, along with considerations for scalability, availability, manageability, and security.
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