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Feature engineering and data preprocessing

Feature engineering and data preprocessing involve transforming raw data into a suitable format for machine learning models by selecting, creating, and optimizing relevant features. These steps improve model accuracy and performance through techniques like normalization, handling missing values, and encoding categorical data.

Question formats in this category:

  • True False Question

  • Grouping

  • Multiple Choice Question

  • Single Choice Question

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Number of questions:

  • Entry: 444

  • Regular: 443

  • Senior: 453

Languages:

  • English

Category used in 1 profiles

Proficiency level: Entry

Category configuration:

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Proficiency level: Regular

Category configuration:

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Proficiency level: Senior

Category configuration:

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