Azure Cluster Configuration for Cost Optimization

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Questions and Answers

What is the primary purpose of using the SMOTE module in Azure Machine Learning Studio?

To analyze the overrepresented cases in a dataset

To increase the number of underrepresented cases in a dataset (correct)

To reduce the number of underrepresented cases in a dataset

To duplicate existing cases in a dataset

Which module should you use to divide data into two distinct datasets in Azure Machine Learning Studio?

Load Trained Model

Partition and Sample (correct)

Assign Data to Clusters

Tune Model-Hyperparameters

What is a common reason for a dataset to be imbalanced?

The data is already balanced

The category is overrepresented in the population

The data is easy to collect

The category is underrepresented in the population (correct)

What is the benefit of using SMOTE over duplicating existing cases?

SMOTE is a better way of increasing the number of rare cases Signup and view all the answers

What is the purpose of the Partition and Sample module in Azure Machine Learning Studio?

To divide data into multiple datasets Signup and view all the answers

What is a common issue in machine learning datasets?

Data is often imbalanced Signup and view all the answers

Which module should you use to handle null rows in a dataset in Azure Machine Learning Studio?

Not specified in the options Signup and view all the answers

What is the context in which the SMOTE module is typically used?

When the class is underrepresented in the population Signup and view all the answers

What is the primary goal of modifying the cluster properties in the given scenario?

To minimize the cost of compute resources when a workload is idle Signup and view all the answers

What is the condition for terminating the training runs in the given scenario?

When the primary metric is lowered by 25 percent or more Signup and view all the answers

What is the purpose of the early termination policy in the given scenario?

To terminate training jobs when a condition is met Signup and view all the answers

What is the goal of the classification model in the given scenario?

To predict if a client will subscribe to a fixed-term deposit Signup and view all the answers

What is the purpose of identifying the feature with the most influence on the predictions of the model?

To understand the importance of each feature Signup and view all the answers

What is the tool used for training the classification model in the given scenario?

nocode AutoML Signup and view all the answers

What is the benefit of using early termination policy in the given scenario?

It minimizes the effort and time to identify the best model Signup and view all the answers

What is the minimum number of instances specified in the cluster definition?

1 Signup and view all the answers

When creating a new Azure Machine Learning workspace with a compute cluster, what is the recommended approach to create the compute cluster?

Asynchronously using the Azure Machine Learning Python SDK v2 Signup and view all the answers

What is the primary requirement for a compute target in Azure Machine Learning?

Enable the use of on-premises compute resources Signup and view all the answers

When training and deploying an Azure Machine Learning solution, what is the role of a compute target?

To support the training and inference of machine learning models Signup and view all the answers

What is the benefit of using autoscaling in an Azure Machine Learning compute target?

Cost savings through dynamic resource allocation Signup and view all the answers

When using the Azure Machine Learning designer, what is the purpose of the Add Rows module?

To create a dataset with the same columns and header row as the input datasets Signup and view all the answers

What is the recommended approach for deploying an Azure Machine Learning solution to production?

Using an AKS inference cluster Signup and view all the answers

What is the benefit of using Azure Machine Learning for data science projects?

Streamlined deployment to production Signup and view all the answers

What is the primary benefit of using on-premises compute resources in Azure Machine Learning?

Meeting specific regulatory requirements Signup and view all the answers

Study Notes

Cluster Properties

A cluster is defined with properties: name, size, min_instances, max_instances, and tier.
In the given example, the properties are:
- name: "mlcluster1"
- size: "STANDARD.DS3.v2"
- min_instances: 1
- max_instances: 4
- tier: "dedicated"

Cost Minimization

To minimize the cost of compute resources, modify the cluster properties.
The goal is to reduce costs when the workload is active or idle.

Hyperparameter Tuning

Azure Machine Learning is used to implement hyperparameter tuning for a model training.
Training runs must terminate when the primary metric is lowered by 25% or more compared to the best performing run.
An early termination policy is needed to terminate training jobs.

Feature Influence

In Azure Machine Learning studio, a classification model is trained with no-code AutoML.
The model predicts if a client will subscribe to a fixed-term deposit.
Identify the feature that has the most influence on the model's predictions for the second highest scoring algorithm.

Compute Cluster Creation

Create a compute cluster asynchronously using the Azure Machine Learning Python SDK v2.
Complete the code segment to create the compute cluster.

Compute Target Configuration

Design an Azure Machine Learning solution using the Python SDK v2.
Train and deploy the solution using a compute target that meets the requirements:
- Enables the use of on-premises compute resources.
- Supports autoscaling.

Dataset Manipulation

Use Azure Machine Learning designer to load datasets into an experiment.
Create a dataset with the same columns and header row as the input datasets and contains all rows from both input datasets.

Classification Task

Solve a classification task with an imbalanced dataset.
Use the Synthetic Minority Oversampling Technique (SMOTE) module in Azure Machine Learning Studio to improve classification accuracy.

Data Division

Use Azure Machine Learning Studio to divide data into two distinct datasets.
The Partition and Sample module with the Stratified split option is used to partition the data.

Handling Null Rows

Handle a dataset that contains null rows in a machine learning model.
Use suitable techniques to handle null values in the dataset.

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Description

Modify Azure cluster properties to minimize compute resource costs while ensuring workload performance. This quiz tests your knowledge of Azure cluster configuration for cost optimization and workload management.