機械学習 CS231nに挑戦!

●自宅でスタンフォード留学!? -ディープラーニングの講義が無料で受講できる

 昨今のオープン化の流れか、多くの大学で講義をウェブに公開しております。大学によって公開の程度は様々ですがMITなどは多くのコンテンツを提供してくれています。

深層学習の講義ではスタンフォード大学のFeiFei Li教授のCS231n (http://cs231n.stanford.edu/)という講義が非常に有名です。というのも、講義の動画、スライド、宿題(Assignment)、プログラムのコードなど多くのコンテンツが無料で利用できるからです。現在は2017年の講義が聴講できます。実際に見てみるとコンテンツの豊富さに驚きました。10万円以上する有料のセミナー以上ではないでしょうか(人のサポートは無いですが)。欧米のオープンイノベーションの考え方には感銘を受けます。日本語であるともっと良いですが、ぜいたくはいえません。

私はこの分野だけでなくプログラミングが苦手なのですが、”挑戦してみたい!”という気持ちひとつで初めて見ようと思います。AI, 機械学習、ディープラーニングなど流行りものに飛びついた感じですが…挫折しないようにがんばります。

この講義は機械学習の中でも画像を扱っており、画像知覚で有名な畳み込みニューラルネットワーク(Convolutional neural network :CNN)を扱っています。

●もくじ

Lesson1 背景

Lesson2 画像分類(Image classification)と線形分類器(linear classifier)

Lesson3 損失関数と最適化

Lesson4 ニューラルネットワーク

Lesson5 畳み込みニューラルネットワーク(Convolutional Nural Network)

Lesson6 ニューラルネットワークの学習Ⅰ

Lesson7 ニューラルネットワークの学習Ⅱ

Lesson8 深層学習のハードウェアとソフトウェア

Lesson9 CNNアーキテクチャ

Lesson10 再帰型ニューラルネットワーク

●用意するもの

PC、ネット環境

プログラミング言語Python用のツールのAnaconda(無料)をインストール

●参考文献

  1. CS231n (Stanford univ.)
  2. ゼロから作るDeep Learning (オライリージャパン)
  3. 直観Deep Learning (オライリージャパン)

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