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name : Deep Learning for Anomaly Detection
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- description : Neural Question Answering
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+ description : Applying deep learning models on the task of anomaly detection
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author : Cloudera Engineer
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specification_version : 1.0
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- prototype_version : 1.0
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+ prototype_version : 1.0
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date : " 2020-09-29"
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- api_version : 1
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+ api_version : 1
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- environment_variables :
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- AWS_ACCESS_KEY :
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- default : " SUPER AWESOME AWS KEY"
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- description : " Access Key ID for accessing S3 bucket"
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- prompt_user : true
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tasks :
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- type : create_job
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name : Install dependencies
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entity_label : install_deps
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script : install_deps.py
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arguments : None
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- short_summary : Job to install dependencies and download training data .
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+ short_summary : Job to install project dependencies .
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environment :
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TASK_TYPE : CREATE/RUN_JOB
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kernel : python3
@@ -29,9 +24,25 @@ tasks:
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long_summary : >-
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Running the job to install dependencies.
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+ - type : create_job
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+ name : Train Model
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+ entity_label : train_model
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+ script : train.py
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+ arguments : None
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+ short_summary : Job to train and export model.
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+ environment :
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+ TASK_TYPE : CREATE/RUN_JOB
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+ kernel : python3
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+
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+ - type : run_job
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+ entity_label : train_model
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+ short_summary : Running model training job.
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+ long_summary : >-
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+ Running the job to train a model.
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+
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- type : start_application
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- name : Application to serve NeuralQA UI
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- subdomain : neuralqa
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+ name : Application to serve Deep Learning for Anomaly Detectionn UI
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+ subdomain : deepad
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script : app.py
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environment_variables :
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TASK_TYPE : START_APPLICATION
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+ !pip3 install - r requirements .txt
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