├── .gitignore ├── MNIST_sample_payload_V4.json ├── README.md ├── autoai └── credit-risk-prediction │ ├── data │ └── german_credit_data_biased_training.csv │ └── model │ └── credit_risk.pickle ├── deep-learning ├── logging │ ├── output_logger.py │ └── output_logger_example.py ├── metrics │ ├── emetrics.py │ ├── emetrics_example.py │ └── keras_metrics_splitter.py └── monitoring │ └── dlmonitor.py ├── keras ├── cars4you_satisfaction │ └── model │ │ └── complain_model_both_datasets.h5.tgz ├── cifar_10 │ └── data │ │ └── README.md ├── import │ └── keras-import-python.ipynb ├── mnist │ ├── MNIST.zip │ ├── data │ │ ├── mnist-tf-test.pkl │ │ ├── mnist-tf-train.pkl │ │ ├── mnist-tf-valid.pkl │ │ └── tf-mnist-test-payload-pkl.json │ ├── emetrics.py │ ├── flow │ │ └── Triple CNN MNIST flow.nnd │ ├── mnist_cnn.py │ ├── mnist_mlp.py │ └── model │ │ └── mnistCNN.h5.tgz └── style │ └── definition │ └── STYLE.zip ├── neunets ├── sample-images │ ├── cifar-10-automobile4.png │ └── cifar-10-bird10.png └── sample-payloads │ ├── cifar-10-automobile4-sample-payload.json │ └── cifar-10-bird10-sample-payload.json ├── pmml └── iris-species │ ├── README.md │ ├── data │ └── iris_scoring_data.json │ └── model │ └── iris_chaid.xml ├── scikit-learn ├── boston │ ├── data │ │ └── housing_data.csv │ └── images │ │ └── boston_houseprice_banner.png ├── custom-transformer-temperature-prediction │ ├── README.md │ ├── dataset │ │ └── GNFUV_USV_Dataset.zip │ ├── libraries │ │ └── linalgnorm-0.1.zip │ └── notebook │ │ └── CustLib-SKL-Model-Save-Deploy-Score.ipynb ├── hand-written-digits-recognition │ ├── README.md │ ├── images │ │ └── numbers_banner-04.png │ ├── meta │ │ └── hand-written-digits-recognition-meta.json │ ├── model │ │ └── hand-written-digits-recognition-model.tgz │ ├── notebook │ │ ├── .ipynb_checkpoints │ │ │ └── From sklearn model to online scoring with python-checkpoint.ipynb │ │ └── From sklearn model to online scoring with python.ipynb │ └── test-data │ │ └── mnist-scikit-learn-test-payload.json └── import-pmml │ ├── scikit-learn-export-pmml-python.ipynb │ ├── scikit-learn-import-python.ipynb │ └── scikit-learn-lr-model-pmml.xml ├── spark ├── cars-4-you │ ├── data │ │ ├── car_rental_feedback_data.csv │ │ └── car_rental_training_data.csv │ └── notebook │ │ └── Use pySpark to predict Business Area and Action.ipynb ├── credit-risk │ ├── data │ │ └── credit_risk_training.csv │ ├── meta │ │ └── credit-risk-meta.json │ └── model │ │ ├── credit-risk-model.tgz │ │ └── credit-risk-pipeline.tgz ├── customer-satisfaction-prediction │ ├── README.md │ ├── data │ │ ├── Telco_customer_churn.csv │ │ ├── WA_Fn UseC_ Telco Customer Churn.csv │ │ └── scoreInput.csv │ ├── images │ │ ├── customersatisfactionadded.png │ │ ├── samplemodels.png │ │ ├── samples.png │ │ ├── users_banner_2-03.png │ │ └── welcomepage.png │ ├── meta │ │ ├── customer-satisfaction-prediction-meta-spark_2.3.0.json │ │ └── customer-satisfaction-prediction-meta.json │ └── model │ │ ├── customer-satisfaction-prediction-model.tgz │ │ └── customer-satisfaction-prediction-pipeline.tgz ├── drug-selection │ ├── README.md │ ├── data │ │ ├── drug_feedback_data.csv │ │ ├── drug_train_data.csv │ │ ├── drug_train_data.json │ │ └── drug_train_data_updated.csv │ ├── images │ │ ├── heart_banner.png │ │ └── learning_banner-05.png │ ├── meta │ │ ├── drug-selection-meta-spark_2.3.0.json │ │ └── drug-selection-meta.json │ └── model │ │ ├── drug-selection-model.tgz │ │ └── drug-selection-pipeline.tgz ├── import-pmml │ ├── pmml-import-python.ipynb │ ├── pmml-import-python_local.ipynb │ ├── spark-mllib-export-pmml-scala.ipynb │ ├── spark-mllib-import-python.ipynb │ └── spark-mllib-lr-model-pmml.xml ├── product-line-prediction │ ├── README.md │ ├── data │ │ └── GoSales_Tx.csv │ ├── images │ │ ├── accessories.svg │ │ ├── camping.svg │ │ ├── golfing.svg │ │ ├── iconss-01.png │ │ ├── image.png │ │ ├── mountaineering.svg │ │ ├── outdoor_protection.svg │ │ ├── productlineadded.png │ │ ├── products_graphics.jpg │ │ ├── products_graphics.png │ │ ├── samplemodels.png │ │ ├── samples.png │ │ └── welcomepage.png │ ├── meta │ │ ├── product-line-prediction-meta-spark_2.3.0.json │ │ └── product-line-prediction-meta.json │ ├── model │ │ ├── product-line-prediction-model.tgz │ │ └── product-line-prediction-pipeline.tgz │ └── notebook │ │ ├── From spark ml model to online scoring with python.ipynb │ │ └── From spark ml model to online scoring with scala.ipynb └── sentiment-prediction │ ├── README.md │ ├── data │ └── trainingTweets.csv │ ├── images │ ├── samplemodels.png │ ├── samples.png │ ├── sentiment_banner_3-04.png │ ├── sentimentpredictionadded.png │ └── welcomepage.png │ ├── meta │ ├── sentiment-prediction-meta-spark_2.3.0.json │ └── sentiment-prediction-meta.json │ └── model │ ├── sentiment-prediction-model.tgz │ └── sentiment-prediction-pipeline.tgz ├── spss ├── Imported_flow_for_customer_satisfaction_prediction.tar.gz ├── TA_tla.str ├── Tutorial_flow.tar.gz ├── big_stream_16_10.str ├── big_stream_16_20_kbp.str ├── car-price-prediction │ ├── README.md │ └── model │ │ └── car-price-prediction.str ├── credit-risk │ ├── data │ │ ├── credit_risk_feedback.csv │ │ ├── credit_risk_scoring.csv │ │ └── credit_risk_training.csv │ └── model │ │ └── german_credit_risk_tutorial.str ├── customer-satisfaction-prediction │ ├── README.md │ ├── data │ │ ├── WA_Fn UseC_ Telco Customer Churn.csv │ │ └── scoreInput.csv │ ├── meta │ │ └── customer-satisfaction-prediction-meta.json │ └── model │ │ ├── customer-satisfaction-prediction-model.tgz │ │ └── customer-satisfaction-prediction.str ├── drug-selection │ ├── README.md │ ├── data │ │ ├── drug_batch_data.csv │ │ └── drug_train_data.csv │ ├── images │ │ └── heart_banner.png │ ├── meta │ │ └── drug-selection-meta.json │ └── model │ │ ├── Drug1n.str │ │ ├── Drug1n.str- │ │ └── Drug1n_capitalized.str ├── financial-performance-prediction │ ├── README.md │ ├── meta │ │ └── financial-performance-prediction-meta.json │ └── model │ │ └── financial-performance-prediction.str ├── profits-forecast │ └── README.md └── ta_sample_stream.str └── tensorflow ├── custom-op-hand-written-digit-recognition ├── README.md ├── libraries │ ├── custom_reshape_pyfunc-0.1.zip │ └── custom_reshape_pyfunc.zip └── notebook │ └── CustLib-TF-PyFunc-Model-Save-Deploy-Score.ipynb ├── distributed-hand-written-digits ├── ddl │ ├── ddl.py │ ├── mnist-train-ddl.py │ ├── tf_ddl.zip │ ├── transform-chkpt.py │ └── transform.py ├── horovod │ ├── manifest.yml │ ├── tensorflow_mnist.py │ └── tf_horovod.zip └── native │ ├── launcher.py │ ├── manifest.yml │ ├── mnist_dist.py │ └── tf_distributed.zip ├── function-deployments-samples ├── mnist-function-deployment-sample-notebook.ipynb ├── mnist-html-canvas-image-data.json └── mnist-tf-hpo-saved-model.tar.gz ├── hand-written-digit-recognition ├── README.md ├── definition │ ├── tf-model-hpo.zip │ ├── tf-model-metrics.zip │ ├── tf-model.zip │ └── tf-softmax-model.zip ├── images │ └── 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