Data Science

Cervical Cancer Risk Prediction Using ML

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The course outlines the learning objectives for understanding XGBoost algorithm theory, performing exploratory data analysis, and implementing XGBoost classifier models using Scikit-Learn.

Key AI Functions:Data Analysis, Machine Learning, Artificial Intelligence(AI), classification

Description for Cervical Cancer Risk Prediction Using ML

  • Comprehend the theory and intuition that underlie the XGBoost algorithm.
  • Conduct an exploratory data analysis
  • Utilize Scikit-Learn to create, train, and assess the XG-Boost classifier model.
  • Level: Beginner

    Certification Degree: Yes

    Languages the Course is Available: 1

    Offered by: On Coursera provided by Beginner

    Duration: 2 hours

    Schedule: Flexible

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