Free Microsoft DP-100 Exam Questions

Question 1

An organization creates and deploys a multi-class image classification deep learning model that uses a set of labeled photographs. The software engineering team reports there is a heavy inferencing load for the prediction web services during the summer. The production web service for the model fails to meet demand despite having a fully-utilized compute cluster where the web service is deployed. You need to improve performance of the image classification web service with minimal downtime and minimal administrative effort. What should you advise the IT Operations team to do?

A : Increase the minimum node count of the compute cluster where the web service is deployed.

B : Create a new compute cluster by using larger VM sizes for the nodes, redeploy the web service to that cluster, and update the DNS registration for the service endpoint to point to the new cluster.

C : Increase the VM size of nodes in the compute cluster where the web service is deployed.

D : Increase the node count of the compute cluster where the web service is deployed.

Answer: D

Question 2

You manage an Azure Machine Learning workspace. You plan to irain a natural language processing (NLP) tew classification model in multiple languages by using Azure Machine learning Python SDK v2. You need to configure the language of the text classification job by using automated machine learning. Which method of the TextClassifkationlob class should you use?

A : set.data

B : set_featurization

C : set_ sweep

D : set_training_parameters

Answer: B

Question 3

A set of CSV files contains sales records. All the CSV files have the same data schema.

Each CSV file contains the sales record for a particular month and has the filename sales.csv. Each file in

stored in a folder that indicates the month and year when the data was recorded. The folders are in an Azure

blob container for which a datastore has been defined in an Azure Machine Learning workspace. The folders

are organized in a parent folder named sales to create the following hierarchical structure:

At the end of each month, a new folder with that month’s sales file is added to the sales folder.

You plan to use the sales data to train a machine learning model based on the following requirements:

You must define a dataset that loads all of the sales data to date into a structure that can be easily

converted to a dataframe.

You must be able to create experiments that use only data that was created before a specific previous

month, ignoring any data that was added after that month.

You must register the minimum number of datasets possible.

You need to register the sales data as a dataset in Azure Machine Learning service workspace.

What should you do?

A : Create a tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file every month. Register the dataset with the name sales_dataset each month, replacing theexisting dataset and specifying a tag named month indicating the month and year it was registered. Usethis dataset for all experiments.

B : Create a tabular dataset that references the datastore and specifies the path 'sales/*/sales.csv', register thedataset with the name sales_dataset and a tag named month indicating the month and year it wasregistered, and use this dataset for all experiments.

C : Create a new tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file every month. Register the dataset with the name sales_dataset_MM-YYYY each monthwith appropriate MM and YYYY values for the month and year. Use the appropriate month-specificdataset for experiments.

D : Create a tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file. Register the dataset with the name sales_dataset each month as a new version and with atag named month indicating the month and year it was registered. Use this dataset for all experiments,identifying the version to be used based on the month tag as necessary.

Answer: B

Question 4

You have an Azure Machine Learning workspace.

You plan to run a job to train a model as an MLflow model output.

You need to specify the output mode of the MLflow model.

Which three modes can you specify? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

A : rw_mount

B : ro_mount

C : upload

D : download

E : direct

Answer: A,C,E

Question 5

You are implementing a machine learning model to predict stock prices. The model uses a PostgreSQL database and requires GPU processing. You need to create a virtual machine that is pre-configured with the required tools. What should you do?

A : Create a Data Science Virtual Machine (DSVM) Windows edition.

B : Create a Geo Al Data Science Virtual Machine (Geo-DSVM) Windows edition.

C : Create a Deep Learning Virtual Machine (DLVM) Linux edition.

D : Create a Deep Learning Virtual Machine (DLVM) Windows edition.

E : Create a Data Science Virtual Machine (DSVM) Linux edition.

Answer: E