IBM C1000-059 Exam Questions

Questions for the C1000-059 were updated on : Jun 07 ,2024

Page 1 out of 5. Viewing questions 1-15 out of 62

Question 1

A new test to diagnose a disease is evaluated on 1152 people, and 106 people have the disease, and
1046 people do not have the disease. The test results are summarized below:

In this sample, how many cases are false positives and false negatives?

  • A. 33 false positives and 81 false negatives
  • B. 81 false positives and 73 false negatives
  • C. 73 false positives and 81 false negatives
  • D. 81 false positives and 33 false negatives
Answer:

A

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Question 2

What is the goal of the backpropagation algorithm?

  • A. to randomize the trajectory of the neural network parameters during training
  • B. to smooth the gradient of the loss function in order to avoid getting trapped in small local minimas
  • C. to scale the gradient descent step in proportion to the gradient magnitude
  • D. to compute the gradient of the loss function with respect to the neural network parameters
Answer:

B

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Reference: https://www.sciencedirect.com/topics/computer-science/backpropagation

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Question 3

With the help of AI algorithms, which type of analytics can help organizations make decisions based
on facts and probability-weighted projections?

  • A. prescriptive analytics
  • B. cognitive analytics
  • C. predictive analytics
  • D. descriptive analytics
Answer:

A

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Reference: https://www.investopedia.com/terms/p/prescriptive-analytics.asp

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Question 4

What is the technique called for vectorizing text data which matches the words in different sentences
to determine if the sentences are similar?

  • A. Cup of Vectors
  • B. Box of Lexicon
  • C. Sack of Sentences
  • D. Bag of Words
Answer:

D

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Reference: https://medium.com/@adriensieg/text-similarities-da019229c894

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Question 5

Which statement is true in the context of evaluating metrics for machine learning algorithms?

  • A. A random classifier has AUC (the area under ROC curve) of 0.5
  • B. Using only one evaluation metric is sufficient
  • C. The F-score is always equal to precision
  • D. Recall of 1 (100%) is always a good result
Answer:

B

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Question 6

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
Answer:

D

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Question 7

Given the following matrix multiplication:

What is the value of P?

  • A. –9
  • B. 17
  • C. 12
  • D. –7
Answer:

C

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

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Question 8

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))
Answer:

CD

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Question 9

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
Answer:

B

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

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Question 10

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 API.
Answer:

C

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

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Question 11

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
Answer:

A

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Question 12

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.
Answer:

B

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Question 13

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

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

D

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

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Question 14

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.
Answer:

CD

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Question 15

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
Answer:

C

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Reference:
https://www.researchgate.net/
publication/318093829_Developing_an_innovative_entity_extraction_method_for_unstructured_da
ta

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