April 2026
Intermediate
586 pages
9h 14m
Japanese
Content preview from AutoMLを学ぶ (Japanese Edition)
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第1部 AutoMLの基礎
自動化された機械学習の力を活用するには、それが何であるか、どこから来たのか、そして内部でどのように機能するのかを理解する必要がある。この基礎知識は、本書の残りの部分を通じて、そして本番環境でAutoMLを適用するキャリア全体を通じて役立つだろう。
このパートでは、まず根本的な質問から始める。AutoMLとは一体何なのか、そしてなぜ現代のML実務者にとって不可欠なものとなったのか。学術研究からエンタープライズ対応プラットフォームへの進化を辿り、実験的なプロトタイプからフォーチュン500企業が日々依存するツールへと成熟していく過程を見ていく。
最も重要なのは、エンドツーエンドのAutoMLパイプラインを詳細に分析することだ。これは、たった1行のコードを実行するだけで自動的に行われる、データ前処理、特徴量エンジニアリング、モデルの選択、ハイパーパラメータの最適化、アンサンブル構築の高度なオーケストレーションである。このパイプラインを理解することは極めて重要だ。これにより、AutoMLはブラックボックスから、デバッグやカスタマイズが可能で、信頼できる透明性の高いシステムへと変わる。
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