Vanishing gradients with RNNs

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deeplearning.ai
4.8(26,197 個評分) | 280K 名學生已註冊
課程 5(共 5 門,深度学习 專項課程
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Natural Language Processing, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Recurrent Neural Network, Attention Models

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4.8(26,197 個評分)
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SD
2018年9月27日

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
2020年4月21日

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.

從本節課中
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.

教學方

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    Andrew Ng

    Instructor
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    Kian Katanforoosh

    Curriculum Developer
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    Younes Bensouda Mourri

    Curriculum developer

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