Building, Training, and Validating Models in Microsoft Azure Flashcards
It is required that a predictions are made weekly to find out which customers are likely default on their loan repayment? A designed model should be deployed to?
Real-time inference end-point
Batch inference end-point
Pipeline
Web service
Batch inference end-point
Calvis Hammond wants to track how a new model will perform upon deployment. Which is the best to do?
Perform AB testing of different models
Deploy new model
Centralize data pipeline
Perform AB testing of different models
A _____ variable changes in response to the _______ variable
Dependent, independent
Independent, dependent
Indepentent, real
Dependent, propriatory
Dependent, independent
We run into modelling difficulties when the
Number of sample space < number of predictors
Number of sample space = number of predictors
Number of sample space > number of predictors
Number of sample space < number of predictors
Participants rated music playing at a fast tempo and at a slow tempo the same in terms of their happiness. What type of hypothesis is this?
Null hypothesis
Alternative hypothesis
Derived hypothesis
Research hypothesis
Null hypothesis
A doctor predicts that a patient is sick, when they are actually in good health. What type of error did the doctor make?
Type II error
This is not an error
Type I
Type I
_________ are not distance-based models and can handle varying ranges of features. Hence, Scaling is not required while modelling trees.
Tree based models
Principal Component Analysis(PCA
k-nearest neighbors
Tree based models
How should you proceed with splitting data when there is an important temporal aspect to the data?
Stratified sampling
Non-random sampling
Random sampling
Non-random sampling
There are several specific types of supervised learning that are represented within Azure Machine Learning Studio (classic): classification, regression, and ___________
Anomaly detection
Clustering
Recommendation
Anomaly detection
“After setting model parameters, you must train the model by using a labeled data set and the Train Anomaly Detection Model training module. “
A model deployed by a data scientist starts experiencing performance degradation. What is the possible cause of this?
Lack of monitoring
Inability to validate
Model drift
Model drift