From a425887f7fdf5ee7835e0bd3a7a8931c6d409f47 Mon Sep 17 00:00:00 2001 From: Manya Sharma <214554783+ManyaS-Git@users.noreply.github.com> Date: Sat, 15 Aug 2026 09:51:37 +0530 Subject: [PATCH] Fix table of contents numbering and 'Deep Leaning' typo in README --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 1749821..48efabf 100644 --- a/README.md +++ b/README.md @@ -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 This repository is arranged as submodules so you can either pull all the tutorials or simply the ones you want. @@ -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 Our best practices are arranged by topic. Each best practice repository includes open source methods, along with considerations for scalability, availability, manageability, and security.