Gradient Checking

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View Syllabus

Skills You'll Learn

Tensorflow, Deep Learning, Mathematical Optimization, hyperparameter tuning

Reviews

4.9 (59,982 ratings)

  • 5 stars
    88.30%
  • 4 stars
    10.56%
  • 3 stars
    0.97%
  • 2 stars
    0.10%
  • 1 star
    0.05%

AM

Oct 8, 2019

Filled StarFilled StarFilled StarFilled StarFilled Star

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

AB

Aug 26, 2021

Filled StarFilled StarFilled StarFilled StarFilled Star

Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.

From the lesson

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.

Taught By

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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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