EXAM C1000-154 REFERENCE | VALID C1000-154 TEST PATTERN

Exam C1000-154 Reference | Valid C1000-154 Test Pattern

Exam C1000-154 Reference | Valid C1000-154 Test Pattern

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Tags: Exam C1000-154 Reference, Valid C1000-154 Test Pattern, New C1000-154 Dumps Files, C1000-154 Test Dumps Demo, C1000-154 Test Vce

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Valid C1000-154 Test Pattern - New C1000-154 Dumps Files

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Earning the IBM Watson Data Scientist certification demonstrates your proficiency in using IBM Watson tools and technologies to build and deploy data science models. IBM Watson Data Scientist v1 certification is highly valued in the industry and can help you advance your career in the field of data science. By passing the C1000-154 Exam, you will join a community of certified IBM Watson Data Scientists who are recognized for their expertise in this field.

IBM Watson Data Scientist v1 Sample Questions (Q63-Q68):

NEW QUESTION # 63
In unsupervised learning, which algorithm is best suited for grouping customers based on their purchase history to target marketing efforts more effectively?

  • A. Support Vector Machines
  • B. Decision Trees
  • C. K-Means Clustering
  • D. Linear Regression

Answer: C


NEW QUESTION # 64
What is a benefit of creating data pipelines to automate the model lifecycle?

  • A. It necessitates frequent manual updates and checks
  • B. Reduces the need for understanding the underlying data
  • C. It provides a structured approach to processing, validating, and deploying models
  • D. Encourages a one-size-fits-all approach to model development

Answer: C


NEW QUESTION # 65
Cloud Pak for Data's integration with Spark allows users to:

  • A. Leverage distributed computing for processing large datasets efficiently
  • B. Avoid using any form of data processing or analysis
  • C. Perform complex computations on small datasets only
  • D. Use Spark exclusively for data visualization purposes

Answer: A


NEW QUESTION # 66
Which type of machine learning algorithm would be most appropriate for predicting house prices based on various features like location, size, and number of bedrooms?

  • A. Dimensionality Reduction
  • B. Classification
  • C. Regression
  • D. Clustering

Answer: C


NEW QUESTION # 67
How does the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology begin its process model?

  • A. Model Building
  • B. Evaluation
  • C. Data Preparation
  • D. Business Understanding

Answer: D


NEW QUESTION # 68
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