Become Microsoft Certified with updated DP-100 exam questions and correct answers
You are implementing a machine learning model to predict stock prices. The model uses a PostgreSQL database and requires GPU processing. You need to create a virtual machine that is pre-configured with the required tools. What should you do?
You are developing deep learning models to analyze semi-structured, unstructured, and structured data types. You have the following data available for model building: Video recordings of sporting events Transcripts of radio commentary about events Logs from related social media feeds captured during sporting events You need to select an environment for creating the model. Which environment should you use?
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are creating a new experiment in Azure Machine Learning Studio. One class has a much smaller number of observations than the other classes in the training set. You need to select an appropriate data sampling strategy to compensate for the class imbalance. Solution: You use the Stratified split for the sampling mode. Does the solution meet the goal?
Note: This question is part of a series of questions that present the same scenario. Each question in
the series contains a unique solution that might meet the stated goals. Some question sets might
have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these
questions will not appear in the review screen.
You create a model to forecast weather conditions based on historical data.
You need to create a pipeline that runs a processing script to load data from a datastore and pass the
processed data to a machine learning model training script.
Solution: Run the following code:

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