Free Microsoft DP-100 Exam Dumps

DragDrop

An organization uses Azure Machine Learning service and wants to expand their use of machine learning.

You have the following compute environments. The organization does not want to create another compute environment.

You need to determine which compute environment to use for the following scenarios.

Which compute types should you use? To answer, drag the appropriate compute environments to the correct scenarios. Each compute environment may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Hotspot

You are using Azure Machine Learning to train machine learning models. You need a compute target on which to remotely run the training script. You run the following Python code:

.

Hotspot

You manage an Azure Machine Learning workspace named workspacel by using the Python SDK v2.

You must register datastores in workspacel for Azure Blob and Azure Data Lake Gen2 storage to meet the following requirements:

* Data scientists accessing the datastore must have the same level of access.

* Access must be restricted to specified containers or folders.

You need to configure a security access method used to register the Azure Blob and Azure Data lake Gen? storage in workspacel. Which security access method should you configure? To answer, select the appropriate options in the answcf area.

NOTE: Each correct selection is worth one point.

Hotspot

You are creating a machine learning model in Python. The provided dataset contains several numerical columns and one text column. The text column represents a product's category. The product category will always be one of the following:

Bikes

Cars

Vans

Boats

You are building a regression model using the scikit-learn Python package.

You need to transform the text data to be compatible with the scikit-learn Python package.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

:

Hotspot

You need to set up the Permutation Feature Importance module according to the model training requirements.

Which properties should you select? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

d

Hotspot

You create an Azure Machine Learning workspace and set up a development environment. You plan to train a deep neural network (DNN) by using the Tensorflow framework and by using estimators to submit training scripts.

You must optimize computation speed for training runs.

You need to choose the appropriate estimator to use as well as the appropriate training compute target configuration.

Which values should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

DragDrop

You are building an intelligent solution using machine learning models.

The environment must support the following requirements:

* Data scientists must build notebooks in a cloud environment

* Data scientists must use automatic feature engineering and model building in machine learning pipelines.

* Notebooks must be deployed to retrain using Spark instances with dynamic worker allocation.

* Notebooks must be exportable to be version controlled locally.

You need to create the environment.

DragDrop

You create a training pipeline using the Azure Machine Learning designer. You upload a CSV file that contains the data from which you want to train your model.

You need to use the designer to create a pipeline that includes steps to perform the following tasks:

* Select the training features using the pandas filter method.

* Train a model based on the naive_bayes.GaussianNB algorithm.

* Return only the Scored Labels column by using the query SELECT [Scored Labels] FROM t1;

Which modules should you use? To answer, drag the appropriate modules to the appropriate locations. Each module name may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

MultipleChoice

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?

Hotspot

You are a lead data scientist for a project that tracks the health and migration of birds. You create a multi-image classification deep learning model that uses a set of labeled bird photos collected by experts. You plan to use the model to develop a cross-platform mobile app that predicts the species of bird captured by app users.

You must test and deploy the trained model as a web service. The deployed model must meet the following requirements:

* An authenticated connection must not be required for testing.

* The deployed model must perform with low latency during inferencing.

* The REST endpoints must be scalable and should have a capacity to handle large number of requests when multiple end users are using the mobile application.

You need to verify that the web service returns predictions in the expected JSON format when a valid REST request is submitted.

Which compute resources should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.