Merge pull request #49401 from ShawnKupfer/WB1695

User Story 399577: Q&M: Retire path and modules: NVidia + ML (2 of 2)

Author: v-dirichards

.openpublishing.redirection.json

@@ -44630,6 +44630,76 @@
       "source_path": "learn-pr/nvidia/create-workspace-resources-getting-started-azure-machine-learning/index.yml",
       "redirect_url": "https://learn.microsoft.com/training/browse/",
       "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/deploy-model-to-nvidia-triton-inference-server/1-introduction.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/deploy-model-to-nvidia-triton-inference-server/2-create-gpu-accelerated-virtual-machine.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/deploy-model-to-nvidia-triton-inference-server/3-install-prerequisites-nvidia-triton-inference-server.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/deploy-model-to-nvidia-triton-inference-server/4-execute-inference-workload-nvidia-triton-inference-server.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/deploy-model-to-nvidia-triton-inference-server/5-knowledge-check.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/deploy-model-to-nvidia-triton-inference-server/6-summary.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/deploy-model-to-nvidia-triton-inference-server/index.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/use-automl-train-labeled-dataset-develop-production-model/1-introduction.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/use-automl-train-labeled-dataset-develop-production-model/2-prepare-jupyter-notebook-workspace.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/use-automl-train-labeled-dataset-develop-production-model/3-configure-jupyter-notebook-execution-environment.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/use-automl-train-labeled-dataset-develop-production-model/4-execute-jupyter-notebook-produce-object-detection-model-automl.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/use-automl-train-labeled-dataset-develop-production-model/5-knowledge-check.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/use-automl-train-labeled-dataset-develop-production-model/6-summary.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "learn-pr/nvidia/use-automl-train-labeled-dataset-develop-production-model/index.yml",
+      "redirect_url": "https://learn.microsoft.com/training/browse/",
+      "redirect_document_id": false
     }
  ]
 }

learn-pr/achievements.yml

@@ -5325,6 +5325,16 @@ achievements:
   title: Write automated tests
   summary: Learn about the types of testing you can do with Rust.
   iconUrl: /training/achievements/rust-automated-tests.svg
+- uid: learn.nvidia.use-automl-train-labeled-dataset-develop-production-model.badge
+  type: badge
+  title: Use AutoML to train a labeled dataset and develop a production model
+  summary: Learn how to use Automated Machine Learning to train a labeled dataset and develop a production object detection model.
+  iconUrl: /training/achievements/setup-configure-nvidia-deepstream-development.svg
+- uid: learn.nvidia.deploy-model-to-nvidia-triton-inference-server.badge
+  type: badge
+  title: Deploy model to NVIDIA Triton Inference Server
+  summary: NVIDIA Triton Inference Server is a multi-framework, open-source software that is optimized for inference. It supports popular machine learning frameworks like TensorFlow, Open Neural Network Exchange (ONNX) Runtime, PyTorch, NVIDIA TensorRT, and more. It can be used for your CPU or GPU workloads. In this module, you deploy your production model to NVIDIA Triton server to perform inference on a cloud-hosted virtual machine.
+  iconUrl: /training/achievements/introduction-nvidia-deepstream-graph-composer-azure.svg
 - uid: learn.nvidia.develop-custom-object-detection-models-with-nvidia-and-azure-machine-learning.trophy
   type: trophy
   title: Develop Custom Object Detection Models with NVIDIA and Azure Machine Learning