April 2020
Intermediate to advanced
344 pages
8h 22m
Japanese
Content preview from Pythonではじめる教師なし学習 ―機械学習の可能性を広げるラベルなしデータの利用
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3
1
章
機械学習エコシステムにおける
教師なし学習の立ち位置
人間や動物が行う学習のほとんどは教師なし学習だ。「知性」全体をケーキだと考えてみよう。
教師なし学習はケーキ本体、教師あり学習はケーキの上のアイシング、強化学習はその上に
乗ったサクランボのようなものだ。われわれはいまのところ、アイシングとサクランボの作り
方は知っているが、ケーキ本体の作り方を知らない。本当の
AI
にいたる道を考えるなら、そ
の前に教師なし学習の問題を解決する必要がある。
−
Yann LeCun
本章では、ルールベースのシステムと機械学習の相違、教師あり学習と教師なし学習の相違、さら
にそれらの利点と欠点について見ていく。
また、一般的な教師あり学習アルゴリズムと教師なし学習アルゴリズムについて説明し、半教師あり
学習や強化学習との関係を見ていく。
1.1
基本的な機械学習用語
さまざまなタイプの機械学習を見ていく前に、これから説明する概念をわかりやすくするために、単
純で広く用いられている機械学習応用システムである、電子メールのスパムフィルタを例として考えて
みよう。これを実現するには、電子メールの集合を受け取り、「スパム」メールと「スパムでない」メー
ルを正確にクラス分類する単純なプログラムを書く必要がある。簡単なクラス分類問題だ。
ここで、機械学習の用語を復習しておこう。この問題では入力変数は電子メールのテキストになる。
入力変数は、特徴量（
feature
）も し く は 予測変数（
predictor
）も し く は 独立変数 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.