CompTIA
Checkpoint
ISC
HP
Dell
EC-Council
EXIN
Fortinet
ITIL®
Juniper
PMI
Microsoft
VMware
Avaya
Google
Salesforce
Amazon
Palo Alto Networks
Certiport
ISC2
All Vendors
  2. Home
  3. Exams
  4. Microsoft
  5. DP-100

Free DP-100 Exam Braindumps (page: 14)

Page 13 of 127
PDF with 512 Questions

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?

  1. Azure Cognitive Services
  2. Azure Data Lake Analytics
  3. Azure HDInsight with Spark MLib
  4. Azure Machine Learning Studio

Answer(s): A

Explanation:

Azure Cognitive Services expand on Microsoft's evolving portfolio of machine learning APIs and enable developers to easily add cognitive features ג€" such as emotion and video detection; facial, speech, and vision recognition; and speech and language understanding ג€" into their applications. The goal of Azure Cognitive
Services is to help developers create applications that can see, hear, speak, understand, and even begin to reason. The catalog of services within Azure Cognitive
Services can be categorized into five main pillars - Vision, Speech, Language, Search, and Knowledge.


Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/welcome



You must store data in Azure Blob Storage to support Azure Machine Learning.
You need to transfer the data into Azure Blob Storage.
What are three possible ways to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  1. Bulk Insert SQL Query
  2. AzCopy
  3. Python script
  4. Azure Storage Explorer
  5. Bulk Copy Program (BCP)

Answer(s): B,C,D

Explanation:

You can move data to and from Azure Blob storage using different technologies:
- Azure Storage-Explorer
- AzCopy
- Python
- SSIS


Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/move-azure-blob



You are moving a large dataset from Azure Machine Learning Studio to a Weka environment.
You need to format the data for the Weka environment.
Which module should you use?

  1. Convert to CSV
  2. Convert to Dataset
  3. Convert to ARFF
  4. Convert to SVMLight

Answer(s): C

Explanation:

Use the Convert to ARFF module in Azure Machine Learning Studio, to convert datasets and results in Azure Machine Learning to the attribute-relation file format used by the Weka toolset. This format is known as ARFF.
The ARFF data specification for Weka supports multiple machine learning tasks, including data preprocessing, classification, and feature selection. In this format, data is organized by entites and their attributes, and is contained in a single text file.


Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/convert-to-arff



You plan to create a speech recognition deep learning model.
The model must support the latest version of Python.
You need to recommend a deep learning framework for speech recognition to include in the Data Science Virtual Machine (DSVM).
What should you recommend?

  1. Rattle
  2. TensorFlow
  3. Weka
  4. Scikit-learn

Answer(s): B

Explanation:

TensorFlow is an open-source library for numerical computation and large-scale machine learning. It uses Python to provide a convenient front-end API for building applications with the framework
TensorFlow can train and run deep neural networks for handwritten digit classification, image recognition, word embeddings, recurrent neural networks, sequence- to-sequence models for machine translation, natural language processing, and PDE (partial differential equation) based simulations.
Incorrect Answers:
A: Rattle is the R analytical tool that gets you started with data analytics and machine learning.
C: Weka is used for visual data mining and machine learning software in Java.
D: Scikit-learn is one of the most useful libraries for machine learning in Python. It is on NumPy, SciPy and matplotlib, this library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction.


Reference:

https://www.infoworld.com/article/3278008/what-is-tensorflow-the-machine-learning-library-explained.html






Post your Comments and Discuss Microsoft DP-100 exam with other Community members: