IBM C1000-059 시험

Question No : 1

What is used to scale large positive values during data cleaning?

• A.division by random numbers
• B.square
• C.logarithm
• D.subtract median

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Question No : 2

What is the first step in creating a custom model in Watson Visual Recognition service?

• A.Test the newly trained model.
• B.Document the errors from the built in models.
• C.Obtain image files containing objects to be classified and organize them into classes.
• D.Use IBM SPSS to create new machine learning classifiers.

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Question No : 3

With only limited labeled data available how might a neural network use case be realized?

• A.by assigning random labels
• B.by increasing the depth of the neural network
• C.by creating random data
• D.by using a customized pre-trained model

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Question No : 4

Which test is applied to determine the relationship between two categorical variables?

• A.paired t-test
• B.chi squared test
• C.z test
• D.t-test

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Explanation:
Reference: https://www.pluralsight.com/guides/testing-for-relationships-between-categorical-variables-using-the-chi-square-test

Question No : 5

What statement is true about UTF-8?

• A.It is encoding for Latin script.
• B.It is rarely used today.
• C.It is encoding for Unicode characters.
• D.It is equal to ASCI

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Explanation:
Reference: https://www.w3.org/International/questions/qa-what-is-encoding

Question No : 6

Which of the following entity extraction techniques would be best for the extraction of telephone numbers from a text document?

• A.complex pattern-based
• B.regex
• C.statistical
• D.dictionary

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Explanation:
Reference: https://www.researchgate.net/publication/318093829_Developing_an_innovative_entity_extraction_method_for_unstructured_data

Question No : 7

Which two statements are correct about deploying machine learning models? (Choose two.)

• A.It allows integration within business applications.
• B.It makes it possible to create reports for management dynamically using specific parameters from executives.
• C.It is critical for achieving high accuracy in training.
• D.It is a necessary step in training and evaluating the performance of the models.
• E.It is only possible on the cloud because they require a large amount of compute resources.

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Question No : 8

Which is a technique that automates the handling of categorical variables?

• A.binary encoding
• B.decoding
• C.autoencoding
• D.one-hot encoding

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Explanation:
Reference: https://hub.packtpub.com/how-to-handle-categorical-data-for-machine-learning-algorithms/

Question No : 9

Which is a preferred approach for simplifying the data transformation steps in machine learning model management and maintenance?

• A.Implement data transformation, feature extraction, feature engineering, and imputation algorithms in one single pipeline.
• B.Do not apply any data transformation or feature extraction or feature engineering steps.
• C.Leverage only deep learning algorithms.
• D.Apply a limited number of data transformation steps from a pre-defined catalog of possible operations independent of the machine learning use case.

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Question No : 10

Determine the number of bigrams and trigrams in the sentence.
"Data is the new oil".

• A.3 bigrams, 3 trigrams
• B.4 bigrams, 4 trigrams
• C.3 bigrams, 4 trigrams
• D.4 bigrams, 3 trigrams

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Question No : 11

After importing a Jupyter notebook and CSV data file into IBM Watson Studio in the IBM Public Cloud project, it is discovered that the notebook code can no longer access the CSV file.
What is the most likely reason for this problem?

• A.CSV files cannot be used as data sources in Watson Studio.
• B.The CSV file was converted to a binary blob and must be converted in the notebook code.
• C.The CSV file is stored in a Cloud Object Storage.
• D.The CSV file is stored in a Watson Machine Learning instance and is only accessible via REST AP

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Explanation:
Reference: https://github.com/IBM/watson-stock-market-predictor/blob/master/README.md

Question No : 12

The formula for recall is given by (True Positives) / (True Positives + False Negatives).



What is the recall for this example?

• A.0.2
• B.0.25
• C.0.5
• D.0.33

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Explanation:
Reference: https://machinelearningmastery.com/precision-recall-and-f-measure-for-imbalanced-classification/

Question No : 13

A neural network is composed of a first affine transformation (affine1) followed by a ReLU non-linearity, followed by a second affine transformation (affine2).
Which two explicit functions are implemented by this neural network? (Choose two.)

• A.y = affine1(ReLU(affine2(x)))
• B.y = max(affine1(x), affine2(x))
• C.y = affine2(ReLU(affine1(x)))
• D.y = affine2(max(affine1(x), 0))
• E.y = ReLU(affine1(x), affine2(x))

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Question No : 14

Given the following matrix multiplication:



What is the value of P?

• A.C9
• B.17
• C.12
• D.C7

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Explanation:
Reference: https://www.mathsisfun.com/algebra/matrix-multiplying.html

Question No : 15

When should median value be used instead of mean value for imputing missing data?

• A.for skewed data
• B.for real numbers
• C.for normally distributed data
• D.for large data sets

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