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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Data Science Solution on Azure |
| Exam Number: | DP-100 |
| Related Certifications: | Microsoft Certified: Azure Data Scientist Associate |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700/1000 |
| Exam Format: | Interactive Tasks, Multiple Choice, Lab, Case Study, Drag and Drop |
| Available Languages: | Korean, Chinese (Simplified), French, Japanese, Spanish, Portuguese, German, English |
| Exam Price: | $165 USD |
| Exam Duration: | 100 minutes |
| Certificate Validity Period: | 1 year |
| Sample Questions: | Microsoft DP-100 Sample Questions |
| Exam Way: | Online proctored exam or test center delivery through Pearson VUE. |
| Pre Condition: | Candidates should have experience with Azure services, Python programming, and machine learning frameworks such as Scikit-Learn, PyTorch, or TensorFlow. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/dp-100/ |
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問題 #18
You use the Azure Machine learning SDK v2 tor Python and notebooks to tram a model. You use Python code to create a compute target, an environment, and a taring script. You need to prepare information to submit a training job.
Which class should you use?
答案：B
問題 #19
You are using C-Support Vector classification to do a multi-class classification with an unbalanced training dataset. The C-Support Vector classification using Python code shown below:
You need to evaluate the C-Support Vector classification code.
Which evaluation statement should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
答案：
解題說明：
Explanation
Box 1: Automatically adjust weights inversely proportional to class frequencies in the input data The "balanced" mode uses the values of y to automatically adjust weights inversely proportional to class frequencies in the input data as n_samples / (n_classes * np.bincount(y)).
Box 2: Penalty parameter
Parameter: C : float, optional (default=1.0)
Penalty parameter C of the error term.
References:
https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html
問題 #20
You need to define an evaluation strategy for the crowd sentiment models.
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.
答案：
解題說明：
1 - Add new features for retraining supervised models.
2 - Evaluate the changes in correlation between model error rate and centriod distance
3 - Filter labeled cases for retraining using the shortest distance from centroids.
Reference:
https://en.wikipedia.org/wiki/Nearest_centroid_classifier
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/sweep-clustering
問題 #21
You create an experiment in Azure Machine Learning Studio- You add a training dataset that contains 10.000 rows. The first 9.000 rows represent class 0 (90 percent). The first 1.000 rows represent class 1 (10 percent).
The training set is unbalanced between two Classes. You must increase the number of training examples for class 1 to 4,000 by using data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.
You need to configure the module.
Which values should you use? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.
答案：
解題說明：
問題 #22
You run a script as an experiment in Azure Machine Learning.
You have a Run object named run that references the experiment run. You must review the log files that were generated during the experiment run.
You need to download the log files to a local folder for review.
Which two code segments can you run to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
答案：B,C
問題 #23
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DP-100試題: https://www.newdumpspdf.com/DP-100-exam-new-dumps.html
此外，這些NewDumps DP-100考試題庫的部分內容現在是免費的：https://drive.google.com/open?id=1rLjJhrxTtTfFG6eXTDJLa4-ls3tRzqMD