IBM C1000-154 EXAMCOLLECTION FREE DUMPS, C1000-154 LATEST MOCK TEST

IBM C1000-154 Examcollection Free Dumps, C1000-154 Latest Mock Test

IBM C1000-154 Examcollection Free Dumps, C1000-154 Latest Mock Test

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IBM Watson Data Scientist certification exam is a comprehensive assessment of a candidate's skills and knowledge in data science. It covers a wide range of topics, including data exploration, data preparation, machine learning, deep learning, and model deployment. C1000-154 exam consists of 60 multiple-choice questions that need to be completed in 90 minutes. C1000-154 Exam is available in English and Japanese, and candidates can take it online or at a Pearson VUE testing center. Passing the exam requires a score of at least 70%. Achieving this certification demonstrates that a candidate has the skills and knowledge needed to work as a data scientist using IBM Watson technologies.

IBM Watson Data Scientist v1 Sample Questions (Q20-Q25):

NEW QUESTION # 20
Which method is used for merging records in SPSS Modeler Merge node that allows specifying a requirement to be satisfied in order for the merge to take place?

  • A. Condition
  • B. Order
  • C. Key
  • D. Filter

Answer: A


NEW QUESTION # 21
A virtual assistant has been developed and deployed based on the Watson Assistant service. The assistant will support customers by answering FAQs (Frequent Answered Questions).
Which metric is a good indicator of the performance of the virtual assistant?

  • A. The F1 score of predicted intents in the Analytics tab
  • B. The Root Mean Squared Error (RMSE) of words
  • C. The Area Under the Curve (AUC)
  • D. Measure escalated calls using A/B testing

Answer: D


NEW QUESTION # 22
What is a key advantage of using supervised learning techniques over unsupervised learning techniques?

  • A. Supervised learning is typically used for prediction with known outcomes, providing clear metrics for model performance.
  • B. Supervised learning can work without any labeled data.
  • C. Supervised learning is more effective for discovering hidden patterns in data without prior labeling.
  • D. Supervised learning algorithms can automatically label data.

Answer: A


NEW QUESTION # 23
Which hyperparameter is NOT commonly adjusted in a deep learning model?

  • A. The color of the model's output
  • B. Activation function
  • C. Learning rate
  • D. Number of layers

Answer: A


NEW QUESTION # 24
When managing data with Cloud Pak for Data Services, what is a common task?

  • A. Reading data from and writing data to Watson Studio
  • B. Avoiding the automation of data processing tasks
  • C. Using the same data management approach for all types of data, regardless of size or format
  • D. Ignoring data security and compliance requirements

Answer: A


NEW QUESTION # 25
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