Dropout Regularization

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강의 계획표 보기

배우게 될 기술

Tensorflow, Deep Learning, Mathematical Optimization, hyperparameter tuning

검토

4.9개(61,434개 평가)

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    10.59%
  • 3 stars
    1%
  • 2 stars
    0.11%
  • 1 star
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JS

2021년 4월 4일

Fantastic course and although it guides you through the course (and may feel less challenging to some) it provides all the building blocks for you to latter apply them to your own interesting project.

AM

2019년 10월 8일

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

수업에서

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.

강사:

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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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