Microsoft DP-100 Practice Test - Questions Answers, Page 7

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

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

A Deep Learning Virtual Machine is a pre-configured environment for deep learning using GPU instances.

Reference:

https://azuremarketplace.microsoft.com/en-au/marketplace/apps/microsoft-ads.dsvm-deep-learning

Caffe2 and PyTorch is supported by Data Science Virtual Machine for Linux.

Microsoft offers Linux editions of the DSVM on Ubuntu 16.04 LTS and CentOS 7.4. Only the DSVM on Ubuntu is preconfigured for Caffe2 and PyTorch.

Incorrect Answers:

D: Caffe2 and PytOCH are only supported in the Data Science Virtual Machine for Linux.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/overview

Azure Container Instances can be used as compute target for testing or development. Use for low-scale CPU-based workloads that require less than 48 GB of RAM.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-deploy-and-where

Use the SMOTE module in Azure Machine Learning Studio (classic) to increase the number of underrepresented cases in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.

You connect the SMOTE module to a dataset that is imbalanced. There are many reasons why a dataset might be imbalanced: the category you are targeting might be very rare in the population, or the data might simply be difficult to collect. Typically, you use SMOTE when the class you want to analyze is under-represented.

Reference:

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

Partition and Sample with the Stratified split option outputs multiple datasets, partitioned using the rules you specified.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample

Remove entire row: Completely removes any row in the dataset that has one or more missing values. This is useful if the missing value can be considered randomly missing.

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

Incorrect Answers:

C, E: The UI is included the Enterprise edition only.

Reference:

https://azure.microsoft.com/en-us/pricing/details/machine-learning/