Language model and sequence generation

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deeplearning.ai
4.8 (15,963 notes) | 140K étudiants inscrits
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Compétences que vous apprendrez

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

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4.8 (15,963 notes)
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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!

À partir de la leçon
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.

Enseigné par

  • 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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