udacity-nd009t-c2-developing-ml-workflow's Issues
project/starter.ipynb function generate_test_case() not working as it currently exists.
The following function, as it exists in the repo, would not work for me or for others, until changing this:
objects = s3.Bucket(bucket).objects.filter("test")
to this:
objects = s3.Bucket(bucket).objects.filter(Prefix="test")
def generate_test_case():
# Setup s3 in boto3
s3 = boto3.resource('s3')
# Randomly pick from sfn or test folders in our bucket
objects = s3.Bucket(bucket).objects.filter("test")
# Grab any random object key from that folder!
obj = random.choice([x.key for x in objects])
return json.dumps({
"image_data": "",
"s3_bucket": bucket,
"s3_key": obj
})
generate_test_case()
Add more details on model training section of the project
lesson4/exercises-solutions.ipynb, sampling_percentage=100 (course content says =34)
The course exercise calls for setting sampling_percentage=34, but this solution code for that exercise sets it to 100.
# SOLUTION
from sagemaker.model_monitor import DataCaptureConfig
capture_uri = f's3://{bucket}/data-capture'
data_capture_config = DataCaptureConfig(
enable_capture=True,
sampling_percentage=100,
destination_s3_uri=capture_uri
)
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