このコースでは、Transformer アーキテクチャと Bidirectional Encoder Representations from Transformers（BERT）モデルの概要について説明します。セルフアテンション機構をはじめとする Transformer アーキテクチャの主要コンポーネントと、それが BERT モデルの構築にどのように使用されているのかについて学習します。さらに、テキスト分類、質問応答、自然言語推論など、BERT を適用可能なその他のタスクについても学習します。このコースの推定所要時間は約 45 分です。
Transformer Models and BERT Model - 日本語版
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Advanced level
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What you'll learn
Transformer アーキテクチャの主要なコンポーネントを理解する
Transformer を使用した BERT モデルの構築方法について学ぶ
BERT を使用して、さまざまな自然言語処理（NLP）タスクを解決する
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Taught in Japanese
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There is 1 module in this course
このモジュールでは、セルフアテンション機構をはじめとする Transformer アーキテクチャの主要コンポーネントと、それが BERT モデルの構築にどのように使用されているのかについて学習します。さらに、テキスト分類、質問応答、自然言語推論など、BERT を適用可能なその他のタスクについても学習します。
What's included
2 videos1 reading1 assignment
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