1Train.py

import os
from azureml.core.authentication import ServicePrincipalAuthentication
from azureml.core import Workspace
import AML 
from azureml.core import Experiment
from sklearn.datasets import load_diabetes
from sklearn.model_selection import train_test_split
from sklearn.linear_model import Ridge
from sklearn.metrics import mean_squared_error
from sklearn.externals import joblib
import math

aml = AML.AML()
ws = aml.ws

print("Found workspace {} at location {}".format(ws.name, ws.location))

experiment = Experiment(workspace=ws, name="diabetes-experiment")

X, y = load_diabetes(return_X_y = True)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=66)


alphas = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]

for alpha in alphas:
    run = experiment.start_logging()
    run.log("alpha_value", alpha)

    model = Ridge(alpha=alpha)
    model.fit(X=X_train, y=y_train)
    y_pred = model.predict(X=X_test)
    rmse = math.sqrt(mean_squared_error(y_true=y_test, y_pred=y_pred))
    run.log("rmse", rmse)

    model_name = "model_alpha_" + str(alpha) + ".pkl"
    filename = "outputs/" + model_name

    joblib.dump(value=model, filename=filename)
    run.upload_file(name=model_name, path_or_stream=filename)
    run.complete()