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Updating Azure Databricks examples

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Roope Astala
2018-09-26 09:32:24 -04:00
parent 9ab092a4d0
commit 8aa287dadf
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databricks/readme.md
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# Azure Databricks - Azure ML SDK Sample Notebooks # Azure Databricks - Azure Machine Learning SDK Sample Notebooks
**NOTE**: With the latest version of our AML SDK, there are some API changes due to which previous version of notebooks will not work. **NOTE**: With the latest version of Azure Machine Learning SDK, there are some API changes due to which previous version of notebooks will not work.
Kindly use this v4 notebooks (updated Sep 18)– if you had installed the AML SDK in your Databricks cluster please update to latest SDK version by installing azureml-sdk[databricks] as a library from GUI. Please remove the previous SDK version and install the latest SDK by installing **azureml-sdk[databricks]** as a PyPi library in Azure Databricks workspace.
**NOTE**: Please create your Azure Databricks cluster as v4.x (high concurrency preferred) with **Python 3** (dropdown). We are extending it to more runtimes asap. **NOTE**: Please create your Azure Databricks cluster as v4.x (high concurrency preferred) with **Python 3** (dropdown).
**NOTE**: Some packages like psutil upgrade libs that can cause a conflict, please install such packages by freezing lib version. Eg. "pstuil **cryptography==1.5 pyopenssl==16.0.0 ipython=2.2.0**" to avoid install error. This issue is related to Databricks and not related to AML SDK. **NOTE**: Some packages like psutil upgrade libs that can cause a conflict, please install such packages by freezing lib version. Eg. "pstuil **cryptography==1.5 pyopenssl==16.0.0 ipython=2.2.0**" to avoid install error. This issue is related to Databricks and not related to AML SDK.
@@ -11,9 +11,9 @@ Kindly use this v4 notebooks (updated Sep 18)– if you had installed the AML SD
The iPython Notebooks have to be run sequentially after making changes based on your subscription. The corresponding DBC archive contains all the notebooks and can be imported into your Databricks workspace. You can the run notebooks after importing .dbc instead of downloading individually. The iPython Notebooks have to be run sequentially after making changes based on your subscription. The corresponding DBC archive contains all the notebooks and can be imported into your Databricks workspace. You can the run notebooks after importing .dbc instead of downloading individually.
This set of notebooks are related to Income prediction experiment based on this [dataset](https://archive.ics.uci.edu/ml/datasets/adult) and demonstrate how to data prep, train and operationalize a Spark ML model with Azure ML Python SDK from within Azure Databricks. For details on SDK concepts, please refer to [Private preview notebooks](https://github.com/Azure/ViennaDocs/tree/master/PrivatePreview/notebooks) This set of notebooks are related to Income prediction experiment based on this [dataset](https://archive.ics.uci.edu/ml/datasets/adult) and demonstrate how to data prep, train and operationalize a Spark ML model with Azure ML Python SDK from within Azure Databricks. For details on SDK concepts, please refer to [notebooks](https://github.com/Azure/MachineLearningNotebooks)
(Recommended) [Azure Databricks AML SDK notebooks](Databricks_AMLSDK_github.dbc) A single DBC package to import all notebooks in your Databricks workspace. (Recommended) [Azure Databricks AML SDK notebooks](Databricks_AMLSDK_github.dbc) A single DBC package to import all notebooks in your Azure Databricks workspace.
01. [Installation and Configuration](01.Installation_and_Configuration.ipynb): Install the Azure ML Python SDK and Initialize an Azure ML Workspace and save the Workspace configuration file. 01. [Installation and Configuration](01.Installation_and_Configuration.ipynb): Install the Azure ML Python SDK and Initialize an Azure ML Workspace and save the Workspace configuration file.
02. [Ingest data](02.Ingest_data.ipynb): Download the Adult Census Income dataset and split it into train and test sets. 02. [Ingest data](02.Ingest_data.ipynb): Download the Adult Census Income dataset and split it into train and test sets.
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06. [Deploy to AKS](04.Deploy_to_AKS_existingImage.ipynb): Deploy model to Azure Kubernetis Service (AKS) with Azure ML Python SDK from an existing Image with model, conda and score file. 06. [Deploy to AKS](04.Deploy_to_AKS_existingImage.ipynb): Deploy model to Azure Kubernetis Service (AKS) with Azure ML Python SDK from an existing Image with model, conda and score file.
Copyright (c) Microsoft Corporation. All rights reserved. Copyright (c) Microsoft Corporation. All rights reserved.
All notebooks in this folder are licensed under the MIT License. All notebooks in this folder are licensed under the MIT License.
Apache®, Apache Spark, and Spark® are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries.