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精通機器學習
book

精通機器學習

by Aurélien Géron
April 2020
Intermediate to advanced
816 pages
18h 32m
Chinese
GoTop Information, Inc.
Content preview from 精通機器學習
544
|
第十六章:用 RNN Attention 處理自然語言
下一章將介紹如何使用自動編碼網路
以無監督的方式來學習深度表達
deep
representation)、
使用生成對抗網路
GAN
來產生圖像
以及其他主題
習題
1. 使用 stateful RNN stateless RNN 的優缺點是什麼?
2. 為什麼大家使用 Encoder–Decoder RNN 而不是一般的 sequence-to-sequence RNN
進行自動翻譯?
3. 如何處理長度不固定的輸入序列?如何處理長度不固定的輸出序列?
4. 什麼是集束搜尋?為何要使用它?你可以用哪種工具來實作它?
5. 什麼是專注機制?它有什麼幫助?
6. Transformer 結構最重要的階層是什麼?它的目的是什麼?
7. 什麼時候要使用抽樣式 softmax
8. Hochreiter Schmidhuber 在探討LSTM 的論文(
https://homl.info/93
)中使用
嵌入式
Reber
語法
embedded
Reber
grammar
)。它們是人工的語法,可產生
BPBTSXXVPSEPE」之類的字串。你可以參考 Jenny Orr 針對這個主題的介紹
https://homl.info/108
)。選擇特定的嵌入式 Reber 語法(例如 Jenny Orr 的網頁介紹
的那一個),接著訓練 RNN 來辨識一個字串是否符合語法。你必須先寫一個函式來
產生一個訓練批次,裡面有大約 ...
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Publisher Resources

ISBN: 9789865024345