Numerical Approximation of Gradients

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Compétences que vous apprendrez

Tensorflow, Deep Learning, Mathematical Optimization, hyperparameter tuning

Avis

4.9 (61,467 évaluations)

  • 5 stars
    88,21 %
  • 4 stars
    10,60 %
  • 3 stars
    1 %
  • 2 stars
    0,11 %
  • 1 star
    0,05 %

CV

23 déc. 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

Thanks.

AS

18 avr. 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

À partir de la leçon

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.

Enseigné par

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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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