「実践者向けディープラーニング勉強会　第三回」に向けた資料。 https://dl4-practitioners.connpass.com/event/128418/ なんとなくエッセンスを理解するための説明。

1. Kazuki Motohashi - Skymind K.K.実践者向けディープラーニング勉強会 第3回 - 15/May/2019
スカイマインド株式会社
本橋 和貴
RNNと⾃然⾔語処理
RNNの基礎からAttention〜BERTの概要まで

2. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.
‣本橋 和貴 @kmotohas
- スカイマインド株式会社
• Deep Learning Engineer (前職ではDL+ROS)
- 素粒⼦物理学実験（LHC-ATLAS実験）出⾝
• 博⼠（理学）
- 好きな定理︓ネーターの定理
2
自己紹介
系に連続的な対称性がある場合はそれに対応する保存則が存在すると述べる定理である。(Wikipedia)

3. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.3
はじめに: L = W
!53
https://www.slideshare.net/ren4yu/ss-84282514

4. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.4
ImageNet データセット と 畳み込みニューラルネット
https://medium.com/@smallfishbigsea/a-walk-through-of-alexnet-6cbd137a5637
ImageNetの大量画像で訓練済みのニューラルネットワークを
特徴抽出機として別の画像認識系タスクに再利用可能

5. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.5!3
15

6. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.6
コンピュータービジョンと自然言語処理
Computer
Vision
Natural
Language
Processing
鳥
りんご
物理世界 記号世界
物理的な光が解析対象 概念的な言葉が解析対象

7. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.7 (引⽤元) https://twitter.com/_Ryobot/status/1050925881894400000/
BERT : 自然言語処理用の汎用特徴抽出機

8. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.
‣ Bidirectional Encoder Representations from Transformers
- 双⽅向のTransformerを⽤いて⾔語表現をエンコードするモデル
8
BERTとは？

9. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.
‣ Googleのニューラル機械翻訳モデル
- RNNを使わずAttention機構のみ利⽤
9
Transformerとは？

10. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.
‣ Agenda
- ⾃然⾔語処理とRNN
- Attention機構
- Transformer/BERTの概要
10
というわけでBERTの雰囲気の理解が目標
https://robomind.co.jp/aivskodomotati3/

11. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.
‣ ⽂書分類 (document categorization)
‣ 機械翻訳 (machine translation)
‣ ⽂章要約 (text summarization)
‣ 質問応答 (question answering)
11
自然言語処理の主要な応用タスク
https://livesalesman.com/why-you-cant-depend-on-machine-translation-for-multilingual-customer-support/
https://towardsdatascience.com/machine-learning-nlp-text-classification-using-scikit-learn-python-and-nltk-c52b92a7c73a
https://towardsdatascience.com/text-summarization-using-deep-learning-6e379ed2e89c
https://towardsdatascience.com/automatic-question-answering-ac7593432842

12. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.
課題
- ⼀般に、⼊⼒の⻑さ (Tx) も出⼒の⻑さ (Ty) もセンテンスごとに異なる
- ある単語の特徴量を学習しても、単語の出現位置が変わると対応できない
12
普通の全結合ニューラルネットワークの課題
・・・ ・・・・・・
x<1>
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x<2>
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x<Tx>
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y<Ty>
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y<1>
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y<2>
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Dogs
Are
Cute
犬
は
かわいい

13. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.13
x<1>
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y<1>
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a<1>
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RNN (Recurrent Neural Network)

14. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.14
x<2>
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y<2>
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RNN (Recurrent Neural Network)

15. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.15
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RNN (Recurrent Neural Network)

16. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.16
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…
RNN (Recurrent Neural Network)

17. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.17
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… ＝
RNN (Recurrent Neural Network)

18. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.18
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Wy<latexit sha1_base64="bhQXL6f3fyKLQ2JedDJwZZQDC4I=">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</latexit>
… ＝
RNN (Recurrent Neural Network)
入力の時系列データを抽象的な文脈情報 (context) としてエンコード

19. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.19
RNN ユニット
x<t>
<latexit sha1_base64="LpX9UMLYcCD4odVg+L+cc/3K4vE=">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</latexit>
a<t 1>
<latexit sha1_base64="5Tnn4ScF2JE1OAwsYnmdKrnrGGo=">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</latexit>
tanh
a<t>
<latexit sha1_base64="/Z5UJ7MrqW44oIbyjfgO+zFdy/Y=">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</latexit>
a<t>
= tanh(W[a<t 1>
, x<t>
] + b)<latexit sha1_base64="PP1Qo41mr4x59N/ZpoAfzuPL9gc=">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</latexit>

20. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.20
RNN ユニット
x<t>
<latexit sha1_base64="LpX9UMLYcCD4odVg+L+cc/3K4vE=">AAAClXicSyrIySwuMTC4ycjEzMLKxs7BycXNw8vHLyAoFFacX1qUnBqanJ+TXxSRlFicmpOZlxpaklmSkxpRUJSamJuUkxqelO0Mkg8vSy0qzszPCympLEiNzU1Mz8tMy0xOLAEKxQsYVMeADYkuSk+KrTbQM7YwMjQ30jHQM7MwNTY2BjIMDc0sjM1qK+KqbUrsamvjBZQN9AzAQAGTYQhlKDNAQUC+wHKGGIYUhnyGZIZShlyGVIY8hhIgO4chkaEYCKMZDBkMGAqAYrEM1UCxIiArEyyfylDLwAXUWwpUlQpUkQgUzQaS6UBeNFQ0D8gHmVkM1p0MtCUHiIuAOhUYVA2uGqw0+GxwwmC1wUuDPzjNqgabAXJLJZBOguhNLYjn75II/k5QVy6QLmHIQOjC6+YShjQGC7BbM4FuLwCLgHyRDNFfVjX9c7BVkGq1msEig9dA9y80uGlwGOiDvLIvyUsDU4NmM3ABI8AQPbgxGWFGeobGekaBJsoOTtCo4GCQZlBi0ACGtzmDA4MHQwBDKNDeaQx7GI4yHGMSZ7JlcmFygyhlYoTqEWZAAUz+AByGmMQ=</latexit>
a<t 1>
<latexit sha1_base64="5Tnn4ScF2JE1OAwsYnmdKrnrGGo=">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</latexit>
tanh
a<t>
<latexit sha1_base64="/Z5UJ7MrqW44oIbyjfgO+zFdy/Y=">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</latexit>
Softmax y<t>
<latexit sha1_base64="NbwxAMmr/oFFYyqcIEhReW7Bbwk=">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</latexit>
a<t>
<latexit sha1_base64="/Z5UJ7MrqW44oIbyjfgO+zFdy/Y=">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</latexit>
a<t>
= tanh(W[a<t 1>
, x<t>
] + b)<latexit sha1_base64="PP1Qo41mr4x59N/ZpoAfzuPL9gc=">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</latexit>

21. 実践者向けディープラーニング勉強会 第3回 - 15/May/2019 Kazuki Motohashi - Skymind K.K.21
x<t>
<latexit sha1_base64="LpX9UMLYcCD4odVg+L+cc/3K4vE=">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</latexit>
a<t 1>
<latexit sha1_base64="5Tnn4ScF2JE1OAwsYnmdKrnrGGo=">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</latexit>
tanh sigmoid
(0, 1)
a<t>
<latexit sha1_base64="/Z5UJ7MrqW44oIbyjfgO+zFdy/Y=">AAAClXicSyrIySwuMTC4ycjEzMLKxs7BycXNw8vHLyAoFFacX1qUnBqanJ+TXxSRlFicmpOZlxpaklmSkxpRUJSamJuUkxqelO0Mkg8vSy0qzszPCympLEiNzU1Mz8tMy0xOLAEKxQsYVMeADYkuSk+KrTbQMzIxMDE10THQMzc2NrEwAjIsjMwtDC1rE+OqbUrsamvjBZRhqhRgqhRgqhQM9QzAQJkBCgLyBZYzxDCkMOQzJDOUMuQypDLkMZQA2TkMiQzFQBjNYMhgwFAAFItlqAaKFQFZmWD5VIZaBi6g3lKgqlSgikSgaDaQTAfyoqGieUA+yMxisO5koC05QFwE1KnAoGpw1WClwWeDEwarDV4a/MFpVjXYDJBbKoF0EkRvakE8f5dE8HeCunKBdAlDBkIXXjeXMKQxWIDdmgl0ewFYBOSLZIj+sqrpn4OtglSr1QwWGbwGun+hwU2Dw0Af5JV9SV4amBo0m4ELGAGwUFbAzQgz0jM01jMKNFF2cIJGBQeDNIMSgwYwvM0ZHBg8GAIYQoH2TmPYw3CU4RiTOJMtkwuTG0QpEyNUjzADCmDyBwCTpZkD</latexit>
˜a<t>
<latexit sha1_base64="bNhwJBuxsGaLv2X53X1hpGg7n7k=">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</latexit>
u<latexit sha1_base64="rPS8OLqVFSCyrVfNSalEwVsFSrE=">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</latexit>
˜a<t>
= tanh(Wa[a<t 1>
, x<t>
] + ba)<latexit sha1_base64="C9WfATp9NLRy1jqxpmgQgD7OXCw=">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</latexit>
update
- The cat, which already ate …, [was] full
- The cats, which already ate …, [were] full
《simplified》GRU (Gated Recurrent Unit) [2014]