Vanishing gradients with RNNs

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deeplearning.ai
4.8(15,971 个评分) | 140K 名学生已注册
课程 5(共 5 门,深度学习 专项课程
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您将学习的技能

Recurrent Neural Network, Artificial Neural Network, Deep Learning, Long Short-Term Memory (ISTM)

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4.8(15,971 个评分)
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SD

Sep 28, 2018

Great hands on instruction on how RNNs work and how they are used to solve real problems. It was particularly useful to use Conv1D, Bidirectional and Attention layers into RNNs and see how they work.

SB

Feb 19, 2018

Loved the course - it was very interesting. It is also pretty complex, so will probably go through it again to review the concepts and how the models work. Thank you for this wonderful course series!

从本节课中
Recurrent Neural Networks
Learn about recurrent neural networks. This type of model has been proven to perform extremely well on temporal data. It has several variants including LSTMs, GRUs and Bidirectional RNNs, which you are going to learn about in this section.

教学方

  • Andrew Ng

    Andrew Ng

    CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain
  • Head Teaching Assistant - Kian Katanforoosh

    Head Teaching Assistant - Kian Katanforoosh

    Lecturer of Computer Science at Stanford University, deeplearning.ai, Ecole CentraleSupelec
  • Teaching Assistant - Younes Bensouda Mourri

    Teaching Assistant - Younes Bensouda Mourri

    Mathematical & Computational Sciences, Stanford University, deeplearning.ai

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