Question 1

You create a multi-class image classification deep learning model that uses a set of labeled images. You

create a script file named train.py that uses the PyTorch 1.3 framework to train the model.

You must run the script by using an estimator. The code must not require any additional Python libraries to be

installed in the environment for the estimator. The time required for model training must be minimized.

You need to define the estimator that will be used to run the script.

Which estimator type should you use?

Options :

A : TensorFlow

B : PyTorch

C : SKLearn

D : Estimator

Answer: B

Question 2

You define a datastore named ml-data for an Azure Storage blob container. In the container, you have a folder

named train that contains a file named data.csv. You plan to use the file to train a model by using the Azure

Machine Learning SDK.

You plan to train the model by using the Azure Machine Learning SDK to run an experiment on local

compute.

You define a DataReference object by running the following code:

You need to load the training data.

Which code segment should you use?

Options :

A :

B :

C :

D :

E :

Answer: E

Question 3

You use the Azure Machine Learning SDK to run a training experiment that trains a classification model and

calculates its accuracy metric.

The model will be retrained each month as new data is available.

You must register the model for use in a batch inference pipeline.

You need to register the model and ensure that the models created by subsequent retraining experiments are

registered only if their accuracy is higher than the currently registered model.

What are two possible ways to achieve this goal? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

Options :

A : Specify a different name for the model each time you register it.

B :

Register the model with the same name each time regardless of accuracy, and always use the latest version of the model in the batch inferencing pipeline

C :

Specify the model framework version when registering the model, and only register subsequent models if this value is higher.

D :

Specify a property named accuracy with the accuracy metric as a value when registering the model, and only register subsequent models if their accuracy is higher than the accuracy property value of the currently registered model.

E :

Specify a tag named accuracy with the accuracy metric as a value when registering the model, and only register subsequent models if their accuracy is higher than the accuracy tag value of the currently registered model.

Answer: D,E

Question 4

You use Azure Machine Learning studio to analyze a dataset containing a decimal column named column1. You need to verity that the column1 values are normally distributed. Which static should you use?

Options :

A : Profile

B : Type

C : Max

D : Mean

Answer: A

Question 5

You have an Azure Machine Learning workspace.

You plan to tune a model hyperparameter when you train the model.

You need to define a search space that returns a normally distributed value.

Which parameter should you use?

Options :

A : QUniform

B : LogUniform

C : Uniform

D : LogNormal

Answer: D