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ml_lr_prediction
KimJeongChul edited this page Apr 29, 2019
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Library : (boto3 / azure.functions, azure.storage.file / google.cloud.storage), sklearn, pandas, time, os, re
- aws : build your deployment package
aws-build-deployment-package -> pandas, sklearn
- google : requirements.txt
google-cloud-storage
gcsfs
scikit-learn
pandas
numpy
- azure : requirements.txt
az==0.1.0.dev1
azure-functions==1.0.0b3
azure-functions-worker==1.0.0b3
grpcio==1.14.2
grpcio-tools==1.14.2
protobuf==3.6.1
six==1.12.0
azure_storage_blob==1.0.0
azure-storage-file==1.0.0
cryptography==2.0
numpy
pandas
scikit-learn
Workload Input: Text
Workload Output: json
Lambda payload(test-event) example:
x : text (example : 'The ambiance is magical. The food and service was nice! The lobster and cheese was to die for and our steaks were cooked perfectly.'
dataset : amazon fine food reviews reviews10mb.csv, reviews20mb.csv, reviews50mb.csv, reviews100mb.csv or https://snap.stanford.edu/data/web-FineFoods.html
model : pretraining logisitc regression model
model_object_key :
{
"x": [TEST_DATA],
"dataset_object_key": [DATASET_OBJECT_KEY],
"dataset_bucket": [DATASET_BUCKET_NAME],
"model_bucket": [MODEL_BUCKET_NAME],
"model_object_key": [MODEL_OBJECT_KEY]
}Lambda Output : prediction, latency