WorksheetsICT ML STUDIO
Total questions: 15
Worksheet time: 30mins
Which of the following statements true for machine learning?
Machine learning is a technique that we can use to create predictive models that continue to be accurate regardless of new and rapid data changes.
Machine learning is a technique we can use to create predictive models based on data relationships
Machine Learning is a technique we can use to create predictive models that do not rely on data relationships.
Machine Learning is a technique we can use to create non-predictive models based on data relationships.
The Azure Machine Learning service has several useful features. Identify these features.
Pipelines
Azure Machine Learning designer
Natural Language Processing
Data and compute management
Which of the following settings are required for when creating a new Azure Machine Learning resource? (Select all the correct answers)
Azure SQL database name
Virtual network name
Workspace name
Resource group
Which of the following are examples of supervised machine learning?(Select all that apply)
Classification
Regression
Clustering
Dimensionality Reduction
Which of the following is a supervised machine learning type used to predict a numerical value?
Density Estimation
Regression
Clustering
Classification
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
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
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?
Enable featurization
Block all algorithms other than GradientBoosting
Set the Primary metric to R2 score
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.
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
Normalize Data
Clean Missing Data
You are using Azure Machine Learning designer to create a training pipeline for a binary classification model. You have 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 was not used for training. Which additional kind of module should you add?
Join Data
Split Data
Select Columns in Dataset
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
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 Iterations to 3
Set Random number seed to 3
Set Number of Centroids to 3
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
Identify the type of learning in which labeled training data is used.
Supervised Learning
Unsupervised Learning
Reinforcement Learning
