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from time import gmtime, strftime experiment_suffix = strftime('%d-%H-%M-%S', gmtime()) experiment_name = f"credit-risk-model-experiment-{experiment_suffix}" The processing script creates a new MLflow active experiment by calling the mlflow.set_experiment() method with the experiment name above. fit_transform(y).
Before you can write scripts that use the Amazon Bedrock API, you’ll need to install the appropriate version of the AWS SDK in your environment. You will not be paid for participation, but the study will reimburse expenses related to participation like transportation, parking, etc. Reimbursement amounts and process are provided.
It serializes these configuration dictionaries (or config dict for short) to their ProtoBuf representation, transports them to the client using gRPC, and then deserializes them back to Python dictionaries. script and a utils.py script described earlier to initialize and set model parameters. The client.py
Amazon Cognito for user authentication with Transport Layer Security (TLS). Each project maintained detailed documentation that outlined how each script was used to build the final model. In many cases, this was an elaborate process involving 5 to 10 scripts with several outputs each. Anu Tumkur is an Architect at athenahealth.
Conversely, the data in your model may be extremely sensitive and highly regulated, so deviation from AWS Key Management Service (AWS KMS) customer managed key (CMK) rotation and use of AWS Network Firewall to help enforce Transport Layer Security (TLS) for ingress and egress traffic to protect against data exfiltration may be an unacceptable risk.
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