Mount Dataset to Azure Machine Learning Compute Instance
import os | |
import pandas as pd | |
from azureml.core import Workspace, Dataset | |
# Connect to Workspace and reference Dataset | |
ws = Workspace.from_config() | |
dataset = ws.datasets["german-credit-train-tutorial"] | |
# Create mountcontext and mount the dataset | |
mount_ctx = dataset.mount() | |
mount_ctx.start() | |
# Get the mount point | |
dataset_mount_folder = mount_ctx.mount_point | |
print(dataset_mount_folder) | |
# List the files in the mount point | |
files = os.listdir(dataset_mount_folder) | |
print(files) | |
# Read some data | |
df = pd.read_csv(os.path.join(dataset_mount_folder, 'german_credit_data.csv')) | |
# Do some more stuff with the data.... | |
# Unmount the dataset from the instance | |
mount_ctx.stop() |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment