Why Regularization Reduces Overfitting?

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Habilidades que você aprenderá

Tensorflow, Deep Learning, Mathematical Optimization, hyperparameter tuning

Avaliações

4.9 (61,593 classificações)

  • 5 stars
    88,21%
  • 4 stars
    10,60%
  • 3 stars
    1%
  • 2 stars
    0,11%
  • 1 star
    0,05%

AM

8 de out de 2019

I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation

CV

23 de dez de 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow

Thanks.

Na lição

Practical Aspects of Deep Learning

Discover and experiment with a variety of different initialization methods, apply L2 regularization and dropout to avoid model overfitting, then apply gradient checking to identify errors in a fraud detection model.

Ministrado por

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    Andrew Ng

    Instructor

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    Kian Katanforoosh

    Senior Curriculum Developer

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    Younes Bensouda Mourri

    Curriculum developer

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