Gradient Checking Implementation Notes

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Skills You'll Learn

Tensorflow, Deep Learning, Mathematical Optimization, hyperparameter tuning

Reviews

4.9 (58,642 ratings)
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HD
Dec 5, 2019

I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.\n\nthe only thing i didn't have completely clear is the barch norm, it is so confuse

CV
Dec 23, 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\n\nThanks.

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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