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Update samples metadata (#924)
* Update samples metadata * Update README.md * Updated Azure Functions * Update README.md
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  • samples
    • csharp
      • end-to-end-apps/ScalableMLModelOnAzureFunction
      • getting-started/AnomalyDetection_PhoneCalls
    • modelbuilder

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‎samples/csharp/end-to-end-apps/ScalableMLModelOnAzureFunction/README.md

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---
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page_type: sample
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name: "Deploy an ML.NET machine learning model to Azure Functions"
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description: "Deploy an ML.NET machine learning model to an Azure Functions serverless environment"
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urlFragment: "mlnet-deploy-serverless-azure-functions"
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languages:
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- csharp
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products:
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- dotnet
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- dotnet-core
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- vs
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- azure
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- azure-functions
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- mlnet
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---
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# Azure Functions Sentiment Analysis Sample
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This sample highlights dependency injection in conjunction with the **.NET Core Integration Package** to build a scalable, serverless Azure Functions application.
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```text
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Negative
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```
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```

‎samples/csharp/getting-started/AnomalyDetection_PhoneCalls/README.md

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---
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page_type: sample
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name: "Detect anomalies in phone call volumes using ML.NET"
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description: "Use ML.NET's time series anomaly detection algorithms to detect anomalies in phone call volumes"
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urlFragment: "mlnet-time-series-anomaly-detection"
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languages:
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- csharp
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products:
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- dotnet
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- dotnet-core
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- vs
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- mlnet
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# Anomaly Detection of Numbers of Phone Calls
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| ML.NET version | API type | Status | App Type | Data type | Scenario | ML Task | Algorithms |

‎samples/modelbuilder/BinaryClassification_Sentiment_Razor/README.md

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---
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page_type: sample
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name: "Train a sentiment analysis machine learning model with ML.NET Model Builder"
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description: "Train a machine learning model to analyze and classify sentiment using ML.NET Model Builder"
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urlFragment: "mlnet-sentiment-analysis-model-builder"
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languages:
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- csharp
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products:
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- dotnet
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- dotnet-core
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- aspnet-core
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- vs
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- vs-ide
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- mlnet
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# Sentiment Analysis: Razor Pages sample optimized for scalability and performance when running/scoring an ML.NET model built with Model Builder (Using the new '.NET Core Integration Package for ML.NET')
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‎samples/modelbuilder/ImageClassification_Azure_LandUse/README.md

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- dotnet-core
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- aspnet-core
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- vs
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- vs-ide
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- windows
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- windows-uwp
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- mlnet
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# Image Classification in Azure with Model Builder

‎samples/modelbuilder/MulticlassClassification_RestaurantViolations/README.md

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page_type: sample
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name: "Categorize the severity of restaurant health violations using ML.NET Model Builder"
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description: "Train a machine learning model to categorize the severity of restaurant health violations using ML.NET Model Builder"
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urlFragment: "mlnet-multiclass-classification-model-builder"
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languages:
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- csharp
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products:
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- dotnet
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- dotnet-core
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- aspnet-core
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- vs
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- vs-ide
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- mlnet
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---
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# Restaurant Violation Inspections
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| ML.NET version | Status | App Type | Data type | Scenario | ML Task | Algorithms |
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|----------------|-------------------------------|-------------|-----------|---------------------|---------------------------|-----------------------------|
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| v1.3.1 | Up-to-date | Console App | Single data sample | Issue Classification | Multiclass classification | Linear Classification |
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| v1.6.0 | Up-to-date | Console App | Single data sample | Issue Classification | Multiclass classification | Linear Classification |
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For a detailed explanation of how to build this application, see the accompanying [tutorial](https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/health-violation-classification-model-builder) on the Microsoft Docs site.
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‎samples/modelbuilder/ObjectDetection_StopSigns/README.md

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page_type: sample
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name: "Train a deep learning object detection model to detect stop signs"
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description: "Train a deep learning object detection model to detect stop signs in images"
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urlFragment: "mlnet-object-detection-model-builder"
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languages:
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- csharp
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products:
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- dotnet
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- dotnet-core
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- aspnet-core
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- vs
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- vs-ide
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- mlnet
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# Stop Sign Object Detection
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| ML.NET version | Status | App Type | Data type | Scenario | ML Task | Algorithms |

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