Basic Models

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강의 계획표 보기

배우게 될 기술

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

검토

4.8개(27,330개 평가)

  • 5 stars
    83.66%
  • 4 stars
    13.03%
  • 3 stars
    2.55%
  • 2 stars
    0.47%
  • 1 star
    0.27%

JS

2020년 7월 12일

Filled StarFilled StarFilled StarFilled StarFilled Star

brilliant course, great quality instruction from Andrew Ng. The only faults are that some of the labs have not been supervised properly being a but buggy and a couple of later lectures were very dry.

SD

2018년 9월 27일

Filled StarFilled StarFilled StarFilled StarFilled Star

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.

수업에서

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.

강사:

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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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