Microsoft Azure AI Fundamentals: Explore visual tools for machine learning Microsoft Quiz Answers

Get Microsoft Azure AI Fundamentals: Explore visual tools for machine learning Microsoft Quiz Answers

Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Learn how to use Azure Machine Learning to create and publish models without writing code.

This learning path helps prepare you for Exam DP-100: Designing and Implementing a Data Science Solution on Azure, Exam AI-900: Microsoft Azure AI Fundamentals.

Prerequisites:

Ability to navigate the Azure portal

Enroll on Microsoft

Module 1: Use Automated Machine Learning in Azure Machine Learning

Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier.

Learning objectives:

Learn how to use the automated machine learning user interface in Azure Machine Learning

Prerequisites:

Ability to navigate the Azure portal

Quiz 1: Knowledge check

Q1. An automobile dealership wants to use historic car sales data to train a machine learning model. The model should predict the price of a pre-owned car based on its make, model, engine size, and mileage. What kind of machine learning model should the dealership use automated machine learning to create?

• Classification
• Regression
• Time series forecasting

Q2. A bank wants to use historic loan repayment records to categorize loan applications as low-risk or high-risk based on characteristics like the loan amount, the income of the borrower, and the loan period. What kind of machine learning model should the bank use automated machine learning to create?

• Classification
• Regression
• Time series forecasting

Q3. You want to use automated machine learning to train a regression model with the best possible R2 score. How should you configure the automated machine learning experiment?

• Set the Primary metric to R2 score
• Block all algorithms other than GradientBoosting
• Enable featurization

Module 2: Create a regression model with Azure Machine Learning designer

Regression is a supervised machine learning technique used to predict numeric values. Learn how to create regression models using Azure Machine Learning designer.

Learning objectives:

Learn how to train and publish a regression model with Azure Machine Learning designer.

Prerequisites:

Ability to navigate the Azure portal

Quiz 1: Knowledge check

Q1. In Azure Machine Learning studio, what can you use to author regression machine learning pipelines using a drag-and-drop interface?

• Notebooks
• Automated machine learning
• Designer

Q2. You are creating a training pipeline for a regression model. You use a dataset that has multiple numeric columns in which the values are on different scales. You want to transform the numeric columns so that the values are all on a similar scale. You also want the transformation to scale relative to the minimum and maximum values in each column. Which module should you add to the pipeline?

• Select Columns in a Dataset
• Clean Missing Data
• Normalize Data

Q3. Why do you split data into training and validation sets?

• Data is split into two sets in order to create two models, one model with the training set and a different model with the validation set.
• Splitting data into two sets enables you to compare the labels that the model predicts with the actual known labels in the original dataset.
• Only split data when you use the Azure Machine Learning Designer, not in other machine learning scenarios.

Module 3: Create a classification model with Azure Machine Learning designer

Classification is a supervised machine learning technique used to predict categories or classes. Learn how to create classification models using Azure Machine Learning designer.

Learning objectives:

Train and publish a classification model with Azure Machine Learning designer

Prerequisites:

Ability to navigate the Azure portal

Quiz 1: Knowledge check

Q1. You’re using Azure Machine Learning designer to create a training pipeline for a binary classification model. You’ve added a dataset containing features and labels, a Two-Class Decision Forest module, and a Train Model module. You plan to use Score Model and Evaluate Model modules to test the trained model with a subset of the dataset that wasn’t used for training. What’s another module should you add?

• Join Data
• Split Data
• Select Columns in Dataset

Q2. You use an Azure Machine Learning designer pipeline to train and test a binary classification model. You review the model’s performance metrics in an Evaluate Model module, and note that it has an AUC score of 0.3. What can you conclude about the model?

• The model can explain 30% of the variance between true and predicted labels.
• The model predicts accurately for 70% of test cases.
• The model performs worse than random guessing.

Q3. You use Azure Machine Learning designer to create a training pipeline for a classification model. What must you do before deploying the model as a service?

• Create an inference pipeline from the training pipeline
• Add an Evaluate Model module to the training pipeline
• Clone the training pipeline with a different name

Module 4: Create a clustering model with Azure Machine Learning designer

Clustering is an unsupervised machine learning technique used to group similar entities based on their features. Learn how to create clustering models using Azure Machine Learning designer.

Learning objectives:

Train and publish a clustering model with Azure Machine Learning designer

Prerequisites:

Ability to navigate the Azure portal

Quiz 1: Knowledge check

Q1. You are using an Azure Machine Learning designer pipeline to train and test a K-Means clustering model. You want your model to assign items to one of three clusters. Which configuration property of the K-Means Clustering module should you set to accomplish this?

• Set Number of Centroids to 3
• Set Random number seed to 3
• Set Iterations to 3

Q2. You use Azure Machine Learning designer to create a training pipeline for a clustering model. Now you want to use the model in an inference pipeline. Which module should you use to infer cluster predictions from the model?

• Score Model
• Assign Data to Clusters
• Train Clustering Model

Conclusion:

I hope this Microsoft Azure AI Fundamentals: Explore visual tools for machine learning Microsoft Quiz Answers would be useful for you to learn something new from this problem. If it helped you then don’t forget to bookmark our site for more Coding Solutions.

This Problem is intended for audiences of all experiences who are interested in learning about Data Science in a business context; there are no prerequisites.

Keep Learning!

More Coding Solutions >>

LeetCode Solutions

Hacker Rank Solutions

CodeChef Solutions