通常1-5営業日で発送：内容紹介
機械学習の考え方とPython実装法がわかる!
分類/回帰問題や深層学習の導入を解説
◎絶妙なバランスで「理論と実践」を展開
◎Pythonライブラリを使いこなす
◎数式・図・Pythonコードを理解する
機械学習の各理論を説明し、Pythonプログラミングによる実装を解説。
初期の機械学習アルゴリズムから、深層学習の導入までを見ていきます。
原著『Python Machine Learning』!
3つのカテゴリーで首位(2016/5/24時点)
Data Modeling & Design/Data Processing/Neural Networks
1章 「データから学習する能力」をコンピュータに与える
2章 分類問題 ―機械学習アルゴリズムのトレーニング
3章 分類問題 ―機械学習ライブラリscikit-learnの活用
4章 データ前処理 ―よりよいトレーニングセットの構築
5章 次元削減でデータを圧縮する
6章 モデル評価とハイパーパラメータのチューニングのベストプラクティス
7章 アンサンブル学習 ―異なるモデルの組み合わせ
8章 機械学習の適用1
| Product # | 4844380605 |
|---|---|
| Weight | 700 g |
| Product package size | 18 x 12 x 3 cm |
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