DP-100 Valid Braindumps Ebook | DP-100 Latest Exam Questions
Do you want to have a new change about your life? If your answer is yes, it is high time for you to use the DP-100 question torrent from our company. As the saying goes, opportunities for those who are prepared. If you have made up your mind to get respect and power, the first step you need to do is to get the DP-100 Certification, because the certification is a reflection of your ability. If you have the DP-100 certification, it will be easier for you to get respect and power. Our company happened to be designing the DP-100 exam question.
Skills measured
- Manage Azure resources for machine learning (25โ30%)
- Run experiments and train models (20โ25%)
- Deploy and operationalize machine learning solutions (35โ40%)
- Implement responsible machine learning (5โ10%)
Microsoft DP-100 certification exam is an essential tool for professionals who want to enhance their skills in data science and Azure data science solutions. DP-100 exam covers a wide range of topics related to data science solutions on Azure and is designed to test the candidateโs ability to design and implement data science solutions using Azure services. The DP-100 certification exam is an excellent tool for professionals who want to advance their careers in data science and demonstrate their expertise in Azure data science solutions.
Microsoft DP-100 (Designing and Implementing a Data Science Solution on Azure) Certification Exam is a highly sought-after certification exam for data scientists and professionals looking to validate their skills in designing and implementing data science solutions on the Azure cloud platform. DP-100 exam measures a candidate's ability to design and implement solutions that use Azure services to support data scientists in building, training, and deploying machine learning models.
>> DP-100 Valid Braindumps Ebook <<
100% Pass 2025 Microsoft High-quality DP-100: Designing and Implementing a Data Science Solution on Azure Valid Braindumps Ebook
Microsoft is one of the international top companies in the world providing wide products line which is applicable for most families and companies, and even closely related to people's daily life. Passing exam with DP-100 valid exam lab questions will be a key to success; will be new boost and will be important for candidates' career path. Microsoft offers all kinds of certifications, DP-100 valid exam lab questions will be a good choice.
Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q192-Q197):
NEW QUESTION # 192
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 an Azure Machine Learning service datastore in a workspace. The datastore contains the following files:
* /data/2018/Q1.csv
* /data/2018/Q2.csv
* /data/2018/Q3.csv
* /data/2018/Q4.csv
* /data/2019/Q1.csv
All files store data in the following format:
id,f1,f2i
1,1.2,0
2,1,1,
1 3,2.1,0
You run the following code:
You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:
Solution: Run the following code:
Does the solution meet the goal?
Answer: A
Explanation:
Use two file paths.
Use Dataset.Tabular_from_delimeted, instead of Dataset.File.from_files as the data isn't cleansed.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-register-datasets
ย
NEW QUESTION # 193
You create a multi-class image classification deep learning model.
The model must be retrained monthly with the new image data fetched from a public web portal. You create an Azure Machine Learning pipeline to fetch new data, standardize the size of images, and retrain the model.
You need to use the Azure Machine Learning SDK to configure the schedule for the pipeline.
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:
Explanation:
Step 1: Publish the pipeline.
To schedule a pipeline, you'll need a reference to your workspace, the identifier of your published pipeline, and the name of the experiment in which you wish to create the schedule.
Step 2: Retrieve the pipeline ID.
Needed for the schedule.
Step 3: Create a ScheduleRecurrence..
To run a pipeline on a recurring basis, you'll create a schedule. A Schedule associates a pipeline, an experiment, and a trigger.
First create a schedule. Example: Create a Schedule that begins a run every 15 minutes:
recurrence = ScheduleRecurrence(frequency="Minute", interval=15)
Step 4: Define an Azure Machine Learning pipeline schedule..
Example, continued:
recurring_schedule = Schedule.create(ws, name="MyRecurringSchedule",
description="Based on time",
pipeline_id=pipeline_id,
experiment_name=experiment_name,
recurrence=recurrence)
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-schedule-pipelines
ย
NEW QUESTION # 194
You create an Azure Machine learning workspace. The workspace contains a folder named src. The folder contains a Python script named script 1 .py.
You use the Azure Machine Learning Python SDK v2 to create a control script. You must use the control script to run script l.py as part of a training job.
You need to complete the section of script that defines the job parameters.
How should you complete the script? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
ย
NEW QUESTION # 195
You are a data scientist building a deep convolutional neural network (CNN) for image classification.
The CNN model you build shows signs of overfitting.
You need to reduce overfitting and converge the model to an optimal fit.
Which two actions should you perform? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. Use training data augmentation.
- B. Add L1/L2 regularization.
- C. Add an additional dense layer with 64 input units.
- D. Reduce the amount of training data.
- E. Add an additional dense layer with 512 input units.
Answer: B,D
Explanation:
B: Weight regularization provides an approach to reduce the overfitting of a deep learning neural network model on the training data and improve the performance of the model on new data, such as the holdout test set.
Keras provides a weight regularization API that allows you to add a penalty for weight size to the loss function.
Three different regularizer instances are provided; they are:
* L1: Sum of the absolute weights.
* L2: Sum of the squared weights.
* L1L2: Sum of the absolute and the squared weights.
D: Because a fully connected layer occupies most of the parameters, it is prone to overfitting. One method to reduce overfitting is dropout. At each training stage, individual nodes are either "dropped out" of the net with probability 1-p or kept with probability p, so that a reduced network is left; incoming and outgoing edges to a dropped-out node are also removed.
By avoiding training all nodes on all training data, dropout decreases overfitting.
Reference:
https://machinelearningmastery.com/how-to-reduce-overfitting-in-deep-learning-with-weight-regularization/
https://en.wikipedia.org/wiki/Convolutional_neural_network
ย
NEW QUESTION # 196
You create a multi-class image classification deep learning experiment by using the PyTorch framework. You plan to run the experiment on an Azure Compute cluster that has nodes with GPU's.
You need to define an Azure Machine Learning service pipeline to perform the monthly retraining of the image classification model. The pipeline must run with minimal cost and minimize the time required to train the model.
Which three pipeline steps should you run 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: Configure a DataTransferStep() to fetch new image data...
Step 2: Configure a PythonScriptStep() to run image_resize.y on the cpu-compute compute target.
Step 3: Configure the EstimatorStep() to run training script on the gpu_compute computer target.
The PyTorch estimator provides a simple way of launching a PyTorch training job on a compute target.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-pytorch
ย
NEW QUESTION # 197
......
Do you feel Microsoft DP-100 exam preparation is tough? FreeDumps desktop and web-based online Designing and Implementing a Data Science Solution on Azure (DP-100) practice test software will give you a clear idea about the final DP-100 test pattern. Practicing with the Microsoft DP-100 practice test, you can evaluate your Designing and Implementing a Data Science Solution on Azure (DP-100) exam preparation. It helps you to pass the Microsoft DP-100 test with excellent results. Microsoft DP-100 imitates the actual DP-100 exam environment. You can take the Designing and Implementing a Data Science Solution on Azure (DP-100) practice exam many times to evaluate and enhance your Microsoft DP-100 exam preparation level.
DP-100 Latest Exam Questions: https://www.freedumps.top/DP-100-real-exam.html
