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下列DP-100练习题是Microsoft DP-100完整题库的一部分. DP-100完整练习题库共有442道题. Examook最新DP-100练习题库可以助您顺利通过考试. 如果您使用我们的题库没有效果, 我们将全额退还您的购买费用. 想要测试和学习Eaxmook DP-100练习题库? 现在开始吧!

 完整 DP-100 练习题库

Microsoft DP-100 练习题库

DP-100 w练习题库的更新日期是 2025-03-13 .

正在练习第 1页 ，共 13 页.

正在练习第 1题 ，共 65 道题

题目#1

HOTSPOT
You are using the Azure Machine Learning Service to automate hyperparameter exploration of your neural network classification model.
You must define the hyperparameter space to automatically tune hyperparameters using random sampling according to following requirements:
✑ The learning rate must be selected from a normal distribution with a mean value of 10 and a standard deviation of 3.
✑ Batch size must be 16, 32 and 64.
✑ Keep probability must be a value selected from a uniform distribution between the range of 0.05 and 0.1.
You need to use the param_sampling method of the Python API for the Azure Machine Learning Service.
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.


A. 

Explanation:
In random sampling, hyperparameter values are randomly selected from the defined search space. Random sampling allows the search space to include both discrete and continuous hyperparameters.
Example:
from azureml.train.hyperdrive import RandomParameterSampling
param_sampling = RandomParameterSampling( {
"learning_rate": normal(10, 3),
"keep_probability": uniform(0.05, 0.1),
"batch_size": choice(16, 32, 64)
}

题目#2

Topic 3, Mix Questions

You plan to run a Python script as an Azure Machine Learning experiment.
The script contains the following code:
import os, argparse, glob
from azureml.core import Run
parser = argparse.ArgumentParser()
parser.add_argument('--input-data',
type=str, dest='data_folder')
args = parser.parse_args()
data_path = args.data_folder
file_paths = glob.glob(data_path + "/*.jpg")
You must specify a file dataset as an input to the script. The dataset consists of multiple large image files and must be streamed directly from its source.
You need to write code to define a ScriptRunConfig object for the experiment and pass the ds dataset as an argument.
Which code segment should you use?

A. arguments = ['--input-data', ds.to_pandas_dataframe()]
B. arguments = ['--input-data', ds.as_mount()]
C. arguments = ['--data-data', ds]
D. arguments = ['--input-data', ds.as_download()]

Explanation:
If you have structured data not yet registered as a dataset, create a TabularDataset and use it directly in your training script for your local or remote experiment.
To load the TabularDataset to pandas DataFrame df = dataset.to_pandas_dataframe()
Note: TabularDataset represents data in a tabular format created by parsing the provided file or list of files.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-with-datasets

题目#3

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 are analyzing a numerical dataset which contains missing values in several columns.
You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.
You need to analyze a full dataset to include all values.
Solution: Calculate the column median value and use the median value as the replacement for any missing value in the column.
Does the solution meet the goal?

A. Yes
B. No

Explanation:
Use the Multiple Imputation by Chained Equations (MICE) method.
References:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3074241/
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

题目#4

DRAG DROP
You need to define a process for penalty event detection.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.


A. 

题目#5

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?

A. Yes
B. No

考题代码: DP-100考题数: 442 道题更新时间:  2025-03-13

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