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The Microsoft DP-100 exam comprises of multiple-choice questions and performance-based tasks that measure the candidate's ability to implement data solutions, analyze data, and create machine learning models using Azure technologies. DP-100 exam is designed to evaluate the candidate's skills in various areas such as data preprocessing, model selection, data visualization, and deployment.
The Microsoft DP-100 Exam consists of various topics, including data exploration and preparation, modeling, deployment, and monitoring. The candidates need to have hands-on experience in these topics to pass the exam successfully. DP-100 exam also covers the use of Azure Machine Learning, Azure Databricks, and other Azure services that are used for implementing data science solutions.
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Microsoft DP-100 exam is a challenging certification exam that requires a thorough understanding of data science and machine learning concepts. It is an excellent way for professionals to demonstrate their skills and knowledge in the field of data science and machine learning and gain a competitive edge in the job market. Passing DP-100 Exam will provide individuals with a valuable certification that is recognized by employers worldwide and open up new opportunities for career growth and advancement.
NEW QUESTION # 78
You create an experiment in Azure Machine Learning Studio- You add a training dataset that contains 10.000 rows. The first 9.000 rows represent class 0 (90 percent). The first 1.000 rows represent class 1 (10 percent).
The training set is unbalanced between two Classes. You must increase the number of training examples for class 1 to 4,000 by using data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.
You need to configure the module.
Which values should you use? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
300
5
NEW QUESTION # 79
You create an Azure Machine Learning workspace. You train a classification model by using automated machine learning (automated ML) in Azure Machine Learning studio. The training data contains multiple classes that have significantly different numbers of samples.
You must use a metric type to avoid labeling negative samples as positive and an averaging method that will minimize the class imbalance.
You need to configure the metric type and the averaging method.
Which configurations should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION # 80
You have the following Azure subscriptions and Azure Machine Learning service workspaces:
You need to obtain a reference to the ml-project workspace.
Solution: Run the following Python code:
Does the solution meet the goal?
Answer: B
NEW QUESTION # 81
You have an Azure Machine Learning workspace.
You plan to use the terminal to configure a compute instance to run a notebook.
You need to add a new R kernel to the compute instance.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
NEW QUESTION # 82
space and set up a development environment. You plan to train a deep neural network (DNN) by using the Tensorflow framework and by using estimators to submit training scripts.
You must optimize computation speed for training runs.
You need to choose the appropriate estimator to use as well as the appropriate training compute target configuration.
Which values should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Tensorflow
TensorFlow represents an estimator for training in TensorFlow experiments.
Box 2: 12 vCPU, 112 GB memory..,2 GPU,..
Use GPUs for the deep neural network.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-train-core/azureml.train.dnn
NEW QUESTION # 83
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