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Merge pull request #107395 from dphansen/davidph-onnx-edge
Update pre-reqs for ONNX on Azure SQL Database Edge
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articles/sql-database-edge/deploy-onnx.md

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ms.service: sql-database-edge
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ms.subservice: machine-learning
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ms.topic: conceptual
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author: ronychatterjee
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ms.author: achatter
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ms.reviewer: davidph
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ms.date: 11/04/2019
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author: dphansen
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ms.author: davidph
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ms.date: 03/26/2020
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---
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# Deploy and make predictions with an ONNX model in SQL Database Edge Preview
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* Open Azure Data Studio and follow these steps to install the packages needed for this quickstart:
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1. Open [New Notebook](https://docs.microsoft.com/sql/azure-data-studio/sql-notebooks) connected to the Python 3 Kernel.
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1. Click **Manage Packages** and under **Add New**, search for **sklearn**, and install the scikit-learn package.
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1. Also, install the **onnxmltools**, **onnxruntime**, **skl2onnx**, and **sqlalchemy** packages.
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1. Click **Manage Packages** and under **Add New**, search for **scikit-learn**, and install the scikit-learn package.
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1. Also, install the **setuptools**, **numpy**, **onnxmltools**, **onnxruntime**, **skl2onnx**, **pyodbc**, and **sqlalchemy** packages.
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* For each script part below, enter it in a cell in the Azure Data Studio notebook and run the cell.
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# y is what we are trying to predict - the median value
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y = df.iloc[:,-1]
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# Split the data frame into features and target
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x_train = df.drop(['MEDV'], axis = 1)
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y_train = df.iloc[:,-1]

articles/sql-database-edge/onnx-overview.md

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ms.service: sql-database-edge
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ms.subservice: machine-learning
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ms.topic: conceptual
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author: ronychatterjee
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ms.author: achatter
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ms.reviewer: davidph
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ms.date: 11/07/2019
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author: dphansen
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ms.author: davidph
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ms.date: 03/26/2020
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---
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# Machine learning and AI with ONNX in SQL Database Edge Preview

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