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Microsoft DP-100 Exam Syllabus Topics:

SectionWeightObjectives
Deploy and retrain models10-15%- Monitor deployed models
  • 1. Track data drift
  • 2. Monitor model performance
- Implement retraining pipelines
  • 1. Manage ML pipelines
  • 2. Create scheduled retraining workflows
Explore data and train models35-40%- Optimize model performance
  • 1. Evaluate models
  • 2. Improve accuracy and performance
- Prepare data for modeling
  • 1. Manage datasets and datastores
  • 2. Ingest and transform data
- Run experiments and train models
  • 1. Perform hyperparameter tuning
  • 2. Track experiments
  • 3. Use automated machine learning
Prepare a model for deployment20-25%- Manage deployment assets
  • 1. Register models
  • 2. Create inference configurations
- Deploy machine learning models
  • 1. Deploy batch inference pipelines
  • 2. Deploy real-time inference endpoints
Design and prepare a machine learning solution20-25%- Design an Azure Machine Learning workspace
  • 1. Configure security and access
  • 2. Manage compute resources
  • 3. Configure workspace resources
- Prepare development environments
  • 1. Use SDKs and notebooks
  • 2. Configure environments

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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q360-Q365):

NEW QUESTION # 360
You manage an Azure Machine Learning workspace named workspace1.
You must register an Azure Blob storage datastore in workspace1 by using an access key. You develop Python SDK v2 code to import all modules required to register the datastore.
You need to complete the Python SDK v2 code to define the datastore.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 361
You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.
The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must identify the feature that has the most influence on the predictions of the model for the second highest scoring algorithm. You must minimize the effort and time to identify the feature.
You need to complete the identification.
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.

Answer:

Explanation:

Explanation:


NEW QUESTION # 362
You manage an Azure Machine Learning workspace. You train a model named model1.
You must identify the features to modify for a differing model prediction result.
You need to configure the Responsible Al (RAI) dashboard for model1.
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.

Answer:

Explanation:

1 - Load and configure the Responsible...
2 - Add the counterfacuals component..
3 - Use the Gather Responsible AI Insights...


NEW QUESTION # 363
You create a binary classification model by using Azure Machine Learning Studio.
You must tune hyperparameters by performing a parameter sweep of the model. The parameter sweep must meet the following requirements:
* iterate all possible combinations of hyperparameters
* minimize computing resources required to perform the sweep
You need to perform a parameter sweep of the model.
Which parameter sweep mode should you use?

Answer: D

Explanation:
Explanation
Explanation:
Maximum number of runs on random grid: This option also controls the number of iterations over a random sampling of parameter values, but the values are not generated randomly from the specified range; instead, a matrix is created of all possible combinations of parameter values and a random sampling is taken over the matrix. This method is more efficient and less prone to regional oversampling or undersampling.
If you are training a model that supports an integrated parameter sweep, you can also set a range of seed values to use and iterate over the random seeds as well. This is optional, but can be useful for avoiding bias introduced by seed selection.
Incorrect Answers:
B: If you are building a clustering model, use Sweep Clustering to automatically determine the optimum number of clusters and other parameters.
C: Entire grid: When you select this option, the module loops over a grid predefined by the system, to try different combinations and identify the best learner. This option is useful for cases where you don't know what the best parameter settings might be and want to try all possible combination of values.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/tune-model- hyperparameters


NEW QUESTION # 364
You create an Azure Machine Learning workspace
You are developing a Python SDK v2 notebook to perform custom model training in the workspace. The notebook code imports all required packages.
You need to complete the Python SDK v2 code to include a training script. environment, and compute information.
How should you complete ten code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point

Answer:

Explanation:

Explanation:


NEW QUESTION # 365
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