Model Interpretability

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Получаемые навыки

Decision Tree, Ensemble Learning, Classification Algorithms, Supervised Learning, Machine Learning (ML) Algorithms

Рецензии

4.9 (оценок: 198)

  • 5 stars
    89,39 %
  • 4 stars
    9,59 %
  • 3 stars
    0,50 %
  • 1 star
    0,50 %

JM

17 июня 2021 г.

The course is very well structured, and the explanations very clear. I would only suggest enhancing the peer-review community since it takes a long time to get a review sometimes.

VS

7 авг. 2022 г.

It's a greate course. I learned a lot, from deeper understanding basic algorithms to more advanced technique such as bagging and model explanability.

Из урока

Modeling Unbalanced Classes

Преподаватели

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    Mark J Grover

    Digital Content Delivery Lead

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    Yan Luo

    Ph.D., Data Scientist and Developer

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    Svitlana (Lana) Kramar

    Data Science Content Developer

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    Joseph Santarcangelo

    Ph.D., Data Scientist at IBM

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    Miguel Maldonado

    Machine Learning Curriculum Developer

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