Dropout Regularization

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您将学习的技能

Tensorflow, Deep Learning, Mathematical Optimization, hyperparameter tuning

审阅

4.9(61,619 个评分)

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AM

Oct 8, 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

XG

Oct 30, 2017

Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.

从本节课中

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.

教学方

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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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