Save/Load Tensorflow & sklearn pipelines from local and AWS S3

After a lot of struggle doing this, I finally found a simple way.

We can write and read Tensorflow and sklearn models/pipelines using joblib.

Local Write / Read

from pathlib import Path
path = Path(<local path>)

# WRITE
with path.open("wb") as f:
    joblib.dump(model, f)

# READ
with path.open("rb") as f:
    f.seek(0)
    model = joblib.load(f)

We can do the same thing on AWS S3 using a boto3 client:

AWS S3 Write / Read

import tempfile
import boto3
import joblib

s3_client = …

aws machinelearning pipelines s3 sklearn tensorflow