Why Regularization Reduces Overfitting?

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Skills You'll Learn

Tensorflow, Deep Learning, Mathematical Optimization, hyperparameter tuning

Reviews

4.9 (57,997 ratings)
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NA
Jan 13, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

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

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

    Curriculum Developer
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    Younes Bensouda Mourri

    Curriculum developer

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