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@ -15,13 +15,13 @@ if you have git older than 2.13 run:
git clone --recursive https://github.com/dciborow/AIArchitecturesAndPractices.git git clone --recursive https://github.com/dciborow/AIArchitecturesAndPractices.git
``` ```
# Architectures <a name="Architectures"></a> # Reference Architectures <a name="Reference Architectures"></a>
| Title | Language | Environment | Design | Description | Status | | Title | Language | Environment | Design | Description | Status |
|----------------------------------------------|-------------|-------------|-------------|-----------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| |----------------------------------------------|-------------|-------------|-------------|-----------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [Deploy Classic ML Model on Kubernetes](https://github.com/Microsoft/MLAKSDeployAML) | Python | CPU | Real-Time Scoring| Train LightGBM model locally using Azure ML, deploy on Kubernetes or IoT Edge for _real-time_ scoring | [![Build Status](https://dev.azure.com/AZGlobal/Azure%20Global%20CAT%20Engineering/_apis/build/status/AI%20CAT/Python-ML-RealTimeServing?branchName=master)](https://dev.azure.com/AZGlobal/Azure%20Global%20CAT%20Engineering/_build/latest?definitionId=21&branchName=master) | [Deploy Classic ML Model on Kubernetes](https://github.com/Microsoft/MLAKSDeployAML) | Python | CPU | Real-Time Scoring| Train LightGBM model locally using Azure ML, deploy on Kubernetes or IoT Edge for _real-time_ scoring | [![Build Status](https://dev.azure.com/AZGlobal/Azure%20Global%20CAT%20Engineering/_apis/build/status/AI%20CAT/Python-ML-RealTimeServing?branchName=master)](https://dev.azure.com/AZGlobal/Azure%20Global%20CAT%20Engineering/_build/latest?definitionId=21&branchName=master)
| [Deploy Deep Learning Model on Kubernetes](https://github.com/Microsoft/AKSDeploymentTutorialAML) | Python | Keras | Real-Time Scoring| Deploy image classification model on Kubernetes or IoT Edge for _real-time_ scoring using Azure ML | [![Build Status](https://dev.azure.com/AZGlobal/Azure%20Global%20CAT%20Engineering/_apis/build/status/AI%20CAT/Python-Keras-RealTimeServing?branchName=master)](https://dev.azure.com/AZGlobal/Azure%20Global%20CAT%20Engineering/_build/latest?definitionId=17&branchName=master) | [Deploy Deep Learning Model on Kubernetes](https://github.com/Microsoft/AKSDeploymentTutorialAML) | Python | Keras | Real-Time Scoring| Deploy image classification model on Kubernetes or IoT Edge for _real-time_ scoring using Azure ML | [![Build Status](https://dev.azure.com/AZGlobal/Azure%20Global%20CAT%20Engineering/_apis/build/status/AI%20CAT/Python-Keras-RealTimeServing?branchName=master)](https://dev.azure.com/AZGlobal/Azure%20Global%20CAT%20Engineering/_build/latest?definitionId=17&branchName=master)
# Practices <a name="Practices"></a> # Best Practices <a name="Best Practices"></a>
| Title | Description | | Title | Description |
|-------|-------------| |-------|-------------|
|[Computer Vision](https://github.com/microsoft/computervision)| Accelerate the development of computer vision applications with examples and best practice guidelines for building computer vision systems |[Computer Vision](https://github.com/microsoft/computervision)| Accelerate the development of computer vision applications with examples and best practice guidelines for building computer vision systems
@ -29,7 +29,7 @@ git clone --recursive https://github.com/dciborow/AIArchitecturesAndPractices.gi
|[Recommenders](github.com/microsoft/recommenders)| Examples and best practices for building recommendation systems, provided as Jupyter notebooks.| |[Recommenders](github.com/microsoft/recommenders)| Examples and best practices for building recommendation systems, provided as Jupyter notebooks.|
# Practices with Architectures <a name="Architectures"></a> # Best Practices with Reference Architectures <a name="Architectures"></a>
| Title | Practice | Language | Environment | Design | Description | Status | | Title | Practice | Language | Environment | Design | Description | Status |
|-------------------------------------------|----------|----------|-------------|-------------|-----------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| |-------------------------------------------|----------|----------|-------------|-------------|-----------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [Building a Real-time Recommendation API](https://github.com/microsoft/recommenders/blob/master/notebooks/05_operationalize/als_movie_o16n.ipynb) | Recommenders | PySpark | CPU | Real-Time Scoring| Walks through the creation of appropriate azure resources, training a recommendation model using Azure Databricks and deploying it as an API.| | [Building a Real-time Recommendation API](https://github.com/microsoft/recommenders/blob/master/notebooks/05_operationalize/als_movie_o16n.ipynb) | Recommenders | PySpark | CPU | Real-Time Scoring| Walks through the creation of appropriate azure resources, training a recommendation model using Azure Databricks and deploying it as an API.|