Data Structure ?
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Data Structure ?
*The above analysis is the result extracted and analyzed by the system, and the specific actual data shall prevail.
README.md
GitHub上のバグ、機能、質問を予見することは、特にGitHubの問題を含む膨大なデータセットが用意されている場合、楽しいことがあります。このハッカソンでは、MachineHackコミュニティに、GitHubのタイトルと本文に基づいてバグ、機能、質問を予測できるアルゴリズムを考え出すよう挑戦させています。テキストデータに関しては、特にデータセットが大きい場合、多くの課題があります。このようなデータセットを分析するには、主に生テキストを表現して機械が理解できるようにするための前処理に関係する多くのことを考慮する必要があります。通常、生の情報を語幹化や語形還元し、その後TF-IDFや単語埋め込みなどを使って表現します。
しかし、TransformerベースのBERTモデルなどの最先端の自然言語処理（NLP）モデルがあれば、TF-IDFやカウントベクトル化のような手動の特徴量エンジニアリングを省略することができます。この短い期間では、様々な事前学習済みモデルを使って、NLPにおけるイメージネットモーメント（転移学習）を活用することをおすすめします。
ハッカソンのリンク - https://www.machinehack.com/hackathons/predict_github_issues_embold_sponsored_hackathon/overview
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- 1. If any data on this site involves infringement, please contact us promptly, and we will arrange for the data to be taken offline.
- 1. The data originates from internet data collection or provided by service providers, and this platform offers users the ability to view and browse datasets.
- 2. This platform serves only as a basic information display for datasets, including but not limited to image, text, video, and audio file types.
- 3. Basic dataset information comes from the original data source or the information provided by the data provider. If there are discrepancies in the dataset description, please refer to the original data source or service provider's address.
- 1. All datasets on this site are copyrighted by their original publishers or data providers.
- 1. If you need to repost data from this site, please retain the original data source URL and related copyright notices.
- 1. If any data on this site involves infringement, please contact us promptly, and we will arrange for the data to be taken offline.
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