DP-100 Exam Dumps : Designing and Implementing a Data Science Solution on Azure

You manage an Azure Machine Learning workspace. The Pylhon scrip! named scriptpy reads an argument named training_data. The trainlng.data argument specifies the path to the training data in a file named datasetl.csv.

You plan to run the scriptpy Python script as a command job that trains a machine learning model.

You need to provide the command to pass the path for the datasct as a parameter value when you submit the script as a training job.

Solution: python script.py –training_data dataset1,csv

Does the solution meet the goal?

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You create an Azure Machine Learning service datastore in a workspace. The datastore contains the following files:

• /data/2018/Q1 .csv

• /data/2018/Q2.csv

• /data/2018/Q3.csv

• /data/2018/Q4.csv

• /data/2019/Q1.csv

All files store data in the following format:

id,M,f2,l

1,1,2,0

2,1,1,1

32,10

You run the following code:

You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:

Solution: Run the following code:

Does the solution meet the goal?

You have an Azure Machine Learning (ML) model deployed to an online endpoint.

You need to review container logs from the endpoint by using Azure Ml Python SDK v2. The logs must include the console log from the inference server with print/log statements from the models scoring script.

What should you do first?