PredictiveModeling/toc at master · mjmanley/PredictiveModeling · GitHub

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<!-- Markdown Navigation -->
{:navgroup: .navgroup}
{:topicgroup: .topicgroup}

{: .toc subcollection="PredictiveModeling" audience="service" href="/docs/services/PredictiveModeling/index.html"}
Machine Learning

    {: .navgroup id="learn"}
    index.md
    ml_getting_access.md
    pm_service_supported_frameworks.md

    {: .topicgroup}
    Spark and Python models
        pm_service_api_spark.md
            pm_service_api_spark_swagger.md
            pm_custom_models.md
            pm_service_api_spark_online.md
            pm_service_api_spark_scoring.md
            pm_service_api_spark_building.md
            pm_service_api_spark_batch.md
            pm_service_api_spark_streaming.md
            pm_service_api_spark_learning_system.md
        pm_service_client_library.md
        pm_service_ui_spark.md
            pm_service_ui_spark_online.md
            pm_service_ui_spark_batch.md
            pm_service_ui_spark_streaming.md
            pm_service_ui_spark_learning_system.md

    {: .topicgroup}
    SPSS models
        using_pm_service.md
        pm_service_api_spss.md
            pm_service_api_spss_online.md
            pm_service_api_manage.md
            pm_service_api_develop.md
            pm_service_api_batch.md
        pm_service_api_new_spss_online.md
    {: .navgroup-end}

    {: .navgroup id="howto"}
    pm_service_api_spark_online.md
    pm_service_api_spark_batch.md
    pm_service_ui_spark_streaming.md
    pm_service_api_spark_building.md
    pm_service_ui_spark.md

    {: .topicgroup}
    Sample notebooks
        [From Spark MLlib model to online scoring with Python](https://apsportal.ibm.com/analytics/notebooks/89492fd6-a641-4819-9176-3d9381561df9/view?access_token=d80bef1a172d1d83d3721b101886337158457281774186f181a2e6a5b57f5ec7)
        [From Spark MLlib model to online scoring with Scala](https://apsportal.ibm.com/analytics/notebooks/c8652d2c-bfc9-4354-8168-f1c9f7f8dfc2/view?access_token=02a83fea8450a452c8de76af98dae078459d0f56810ddef4f4c62d5bc4fc72cf)
        [From Spark MLlib model to batch scoring with python](https://apsportal.ibm.com/analytics/notebooks/5e4963d9-faea-455d-a7db-ff6302d1d8f5/view?access_token=5d23d36be72dea35ebbde9b4b5f4a16d0053ee898f1ab2ab73cf1301ce9322be)
        [From Spark MLlib model to stream scoring with python](https://apsportal.ibm.com/analytics/notebooks/913a7daa-cf39-414d-9017-3a7840a53c59/view?access_token=f1ebc10873a226f248f744b26ee7f71d53c81d5752b9d940e23a33518a3e115d)
        [From Spark MLlib model to learning system with python](https://dataplatform.ibm.com/analytics/notebooks/57bd0753-ccee-42bd-9d11-099a981e4fbe/view?access_token=40b77775b209dab516811a695ba1d5dbcab2dfb260c910daf3d985c9d4570325)
        [From scikit-learn to online scoring with Python](https://apsportal.ibm.com/analytics/notebooks/5215a61a-16d7-4fa2-b060-e3e243ceebe3/view?access_token=70f48c95c5571a614ce97484d3f168b1d9b6aeebce015187d3d77ce6038f025e)
        [From XGBoost scikit-learn wrapper model to online scoring with python](https://apsportal.ibm.com/analytics/notebooks/20c1c2d6-6a51-4bdc-9b2c-0e3f2bef7376/view?access_token=52b727bd6515bd687cfd88f929cc7869b0ea420e668b2730c6870e72e029f0d1)
        [From XGBoost native model to online scoring with python](https://apsportal.ibm.com/analytics/notebooks/7a9ce22f-18cb-44aa-aaad-b3a8e839b543/view?access_token=263c7adf1c08bac182e15125e4fc667a1d44fca12b1af8b2aafe19ec7818755d)
        [From SPSS stream to batch scoring with Python](https://apsportal.ibm.com/analytics/notebooks/9d7ce38e-9417-4c76-a6b9-5bc8cf40938a/view?access_token=5ca87e3007804e5b2bbbce77c20e99ac3c164d66f2d28dfffb54aa365caaef37)
        [From local Spark MLlib model to cloud with watson-machine-learning-client](https://apsportal.ibm.com/analytics/notebooks/1fed143e-1877-42bd-b927-7d366e73745b/view?access_token=4b39718f9e1f1de55e6e67e8dcbb5f0cac848f390d73478d0dea9c1a8af24550)
        [From local scikit-learn model to cloud with watson-machine-learning-client](https://dataplatform.ibm.com/analytics/notebooks/15b46bd5-dde2-4d59-9d7d-51cc0b860c8b/view?access_token=d8711ad6ae84b3a9c60d43966f961f66adc2c5b89fec18f24c85e40774080e9a)

    {: .topicgroup}
    Sample applications
        [Customer interest in sport products prediction using Spark MLlib](https://github.com/pmservice/product-line-prediction)
        [Financial performance prediction of a company using SPSS](https://github.com/pmservice/financial-performance-prediction)
        [Best drug selection for a heart problem using SPSS](https://github.com/pmservice/drug-selection)
        [Clothes sales profits prediction using SPSS](https://github.com/pmservice/profits-forecast)
        [Customer churn prediction using SPSS](https://github.com/pmservice/customer-satisfaction-prediction)
    {: .navgroup-end}

    {: .navgroup id="reference"}
    [Machine Learning REST API](http://watson-ml-api.mybluemix.net)
    [Machine Learning API client libraries](pm_service_client_library.html)
    ml_troubleshooting.md
    wml_quota_policy.md
    [Supported SPSS Modeler nodes](https://www.ibm.com/support/knowledgecenter/SSWLVY_3.0.1/analytic_server_user-guide_ddita/analytic_server/ae_modeler_integration_supported_nodes.html)

    {: .topicgroup}
    Related tools
        [IBM SPSS Modeler Knowledge Center](https://www.ibm.com/support/knowledgecenter/SS3RA7)
        [IBM Data Science Experience](https://datascience.ibm.com)
    {: .navgroup-end}