DP-100 Practice Test

Question 86

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 a data scientist using Azure Machine Learning Studio. You need to normalize values to produce an output column into bins to predict a target column. Solution: Apply an Equal Width with Custom Start and Stop binning mode. Does the solution meet the goal?

1. Yes
2. No

Question 87

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 a data scientist using Azure Machine Learning Studio. You need to normalize values to produce an output column into bins to predict a target column. Solution: Apply a Quantiles binning mode with a PQuantile normalization. Does the solution meet the goal?

1. Yes
2. No

Question 88

You are evaluating a Python NumPy array that contains six data points defined as follows: data = [10, 20, 30, 40, 50, 60] You must generate the following output by using the k-fold algorithm implantation in the Python Scikit-learn machine learning library: train: [10 40 50 60], test: [20 30] train: [20 30 40 60], test: [10 50] train: [10 20 30 50], test: [40 60] You need to implement a cross-validation to generate the output. How should you complete the code segment? To answer, select the appropriate code segment in the dialog box in the answer area. NOTE: Each correct selection is worth one point. Hot Area:

Question 89

You are with a time series dataset in Azure Machine Learning Studio. You need to split your dataset into training and testing subsets by using the Split Data module. Which splitting mode should you use?

1. Recommender Split
2. Regular Expression Split
3. Relative Expression Split
4. Split Rows with the Randomized split parameter set to true

Question 90

You are preparing to build a deep learning convolutional neural network model for image classification. You create a script to train the model using CUDA devices. You must submit an experiment that runs this script in the Azure Machine Learning workspace. The following compute resources are available: ✑ a Microsoft Surface device on which Microsoft Office has been installed. Corporate IT policies prevent the installation of additional software ✑ a Compute Instance named ds-workstation in the workspace with 2 CPUs and 8 GB of memory ✑ an Azure Machine Learning compute target named cpu-cluster with eight CPU-based nodes ✑ an Azure Machine Learning compute target named gpu-cluster with four CPU and GPU-based nodes You need to specify the compute resources to be used for running the code to submit the experiment, and for running the script in order to minimize model training time. Which resources should the data scientist use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. Hot Area: