February 2019
Beginner to intermediate
224 pages
3h 38m
Japanese
Overview
本書は、機械学習モデルの性能を向上させるために、データから良い特徴量を作る特徴量エンジニアリングについて解説します。前半では初学者に向けて、数値、テキスト、カテゴリ変数の基本的な取り扱い方を説明し、後半では特徴量ハッシング、ビンカウンティング、PCAによるデータの圧縮、さらに非線形特徴量とモデルスタッキング、画像特徴量抽出と深層学習による自動特徴学習などの高度なテーマを扱います。特徴量エンジニアリングを使いこなし、機械学習モデルの性能を最大限に引き出したいエンジニア必携の一冊です。
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