Decision tree model

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Получаемые навыки

Artificial Neural Network, Xgboost, Tensorflow, Tree Ensembles, Advice for Model Development

Рецензии

4.9 (оценок: 337)

  • 5 stars
    91,69 %
  • 4 stars
    7,71 %
  • 2 stars
    0,29 %
  • 1 star
    0,29 %

BS

29 июля 2022 г.

This course is even better and more accessible in this new format. This instance is quite complicated, requires some good python/numpy knowledge but the math is not so overwhelming.

MM

22 июня 2022 г.

Excellent course, although it would have been good to talk more about backward propagation, after finishing this course this is the only point that is left unclear in my mind.

Из урока

Decision trees

This week, you'll learn about a practical and very commonly used learning algorithm the decision tree. You'll also learn about variations of the decision tree, including random forests and boosted trees (XGBoost).

Преподаватели

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    Andrew Ng

    Instructor

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    Eddy Shyu

    Curriculum Architect

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    Aarti Bagul

    Curriculum Engineer

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    Geoff Ladwig

    Curriculum Engineer

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