DP-100T01: Designing and Implementing a Data Science Solution on Azure Quiz Questions and Answers
Precision is the most commonly used error metric in the classification mechanism. What is the range for it?
Answer :
0-1
This task provides your data to the configured model to learn from patterns and create statistics that can be used for predictions.
Answer :
Train
It is a process of generating values based on a trained Machine Learning model, given some new input data.
Answer :
Scoring
This feature improves Machine Learning results and predictive performance by combining multiple models instead of single models.
Answer :
Ensemble Models
You are using the Azure Machine Learning Python SDK to write code for an experiment. You must log metrics from each run of the experiment and be able to retrieve them easily from each run. What should you do?
Answer :
Use the log methods of the Run class to record named metrics
You have uploaded some data files to a folder in a blob container and registered the blob container as a datastore in your Azure Machine Learning workspace. You want to run a script as an experiment that loads the data files and trains a model. What should you do?
Answer :
Create a data reference for the datastore location and pass it to the script as a parameter
You are creating a pipeline that includes two steps. Step 1 preprocesses some data, and step 2 uses the preprocessed data to train a model. What object should you use to pass data from step 1 to step 2 and create a dependency between these steps?
Answer :
OutputFileDatasetConfig
You have trained a classification model, and you want to quantify the influence of each feature on a specific individual prediction. What should you examine?
Answer :
Local feature importance
You have trained a model using a dataset containing data that was collected last year. As this year progresses, you will collect new data. You want to track any changing data trends that might affect the performance of the model. What should you do?
Answer :
Collect the new data in a separate dataset and create a Data Drift Monitor with the training dataset as a baseline and the new dataset as a target
You are creating a data drift monitor. You want to automatically notify the data science team if a significant change in data distribution is detected. What must you do?
Answer :
Define an Alert Configuration and set a drift threshold value
