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Compétences que vous apprendrez

Natural Language Processing, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Recurrent Neural Network, Attention Models

Avis

4.8 (26,883 évaluations)

  • 5 stars
    83,64 %
  • 4 stars
    13,09 %
  • 3 stars
    2,51 %
  • 2 stars
    0,47 %
  • 1 star
    0,26 %

SD

27 sept. 2018

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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.

MH

21 avr. 2020

Filled StarFilled StarFilled StarFilled StarFilled Star

Very good. I have no complaints. I though instruction was very clear. Assignments were very helpful and challenging enough that I learned something, but not so challenging that I got stuck too often.

À partir de la leçon

Sequence Models & Attention Mechanism

Augment your sequence models using an attention mechanism, an algorithm that helps your model decide where to focus its attention given a sequence of inputs. Then, explore speech recognition and how to deal with audio data.

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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