USEFUL EXAMS DP-100 TORRENT, PRACTICE DP-100 ENGINE

Useful Exams DP-100 Torrent, Practice DP-100 Engine

Useful Exams DP-100 Torrent, Practice DP-100 Engine

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How to book the DP-100 Exam

These are following steps for registering the DP-100 exam.Step 1: Visit to Microsoft Exam RegistrationStep 2: Signup/Login to MICROSOFT accountStep 3: Search for MICROSOFT DP-100 Certifications ExamStep 4: Select Date and Center of examination and confirm with payment value of $165

The DP-100 exam covers a wide range of topics, including data exploration and preparation, modeling, visualization, and deployment. Candidates will be tested on their ability to use various Azure tools and services, such as Azure Machine Learning, Azure Databricks, and Azure Cognitive Services, to build end-to-end data science solutions. They will also need to demonstrate their understanding of the principles of machine learning, statistical analysis, and data visualization, as well as their ability to communicate insights and findings to stakeholders. Passing DP-100 Exam is a significant achievement for data science professionals who want to showcase their expertise in Azure-based data science solutions.

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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q111-Q116):

NEW QUESTION # 111
You create an Azure Machine Learning workspace 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:

Reference:
https://docs.microsoft.com/en-us/python/api/azureml-train-core/azureml.train.dnn


NEW QUESTION # 112
You need to define a modeling strategy for ad response.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation:

Step 1: Implement a K-Means Clustering model
Step 2: Use the cluster as a feature in a Decision jungle model.
Decision jungles are non-parametric models, which can represent non-linear decision boundaries.
Step 3: Use the raw score as a feature in a Score Matchbox Recommender model The goal of creating a recommendation system is to recommend one or more "items" to "users" of the system.
Examples of an item could be a movie, restaurant, book, or song. A user could be a person, group of persons, or other entity with item preferences.
Scenario:
Ad response rated declined.
Ad response models must be trained at the beginning of each event and applied during the sporting event.
Market segmentation models must optimize for similar ad response history.
Ad response models must support non-linear boundaries of features.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/multiclass-decision-jungle
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/score-matchbox-recommende


NEW QUESTION # 113
You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.
The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must preview the data profile in Azure Machine Learning studio once the dataset is created.
You need to train the model.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

1 - Create a file dataset.
2 - Create a compute cluster.
3 - Create an experiment.
4 - Create an automated MLjob.


NEW QUESTION # 114
You arc I mating a deep learning model to identify cats and dogs. You have 25,000 color images.
You must meet the following requirements:
* Reduce the number of training epochs.
* Reduce the size of the neural network.
* Reduce over-fitting of the neural network.
You need to select the image modification values.
Which value should you use? To answer, select the appropriate Options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 115
You are producing a multiple linear regression model in Azure Machine Learning Studio.
Several independent variables are highly correlated.
You need to select appropriate methods for conducting effective feature engineering on all the data.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation:
Step 1: Use the Filter Based Feature Selection module
Filter Based Feature Selection identifies the features in a dataset with the greatest predictive power.
The module outputs a dataset that contains the best feature columns, as ranked by predictive power. It also outputs the names of the features and their scores from the selected metric.
Step 2: Build a counting transform
A counting transform creates a transformation that turns count tables into features, so that you can apply the transformation to multiple datasets.
Step 3: Test the hypothesis using t-Test
References:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/studio-module-reference/filter-based-feature-selection
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/build-counting-transform


NEW QUESTION # 116
......

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