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『ゼロから作る Deep Learning ❹』(O'Reilly Japan, 2022)
| Date | Stars |
|---|---|
| 2026-07-31 | 675 |
| 2026-08-06 | 675 |
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[<img src="https://raw.githubusercontent.com/oreilly-japan/deep-learning-from-scratch-4/images/deep-learning-from-scratch-4.png" width="200px">](https://www.amazon.co.jp/dp/4873119758) 書籍『[ゼロから作るDeep Learning ❹ 強化学習編](https://www.amazon.co.jp/dp/4873119758)』(オライリー・ジャパン)のサポートサイトです。本書籍で使用するソースコードがまとめられています。 ## ニュース <a href="https://koki0702.github.io/dezero-p100/"><img src="https://raw.githubusercontent.com/oreilly-japan/deep-learning-from-scratch-4/images/p100.png" height="200px"></a> 本書の内容を確認するための「強化学習100題」を用意しています。 https://koki0702.github.io/dezero-p100/ ## ファイル構成 |フォルダ名 |説明 | |:-- |:-- | |ch01 |1章で使用するソースコード | |... |... | |ch09 |9章で使用するソースコード | |common |共通で使用するソースコード | |notebooks |Jupyter Notebook形式のソースコード | |pytorch |PyTorchに移植したソースコード | ## Jupyter Notebook 本書のコードはJupyter Notebookでも用意しています。次の表にあるボタンをクリックすることで、Google ColabやKaggle Notebookなどのクラウドサービス上でNotebookを実行することができます。 | 章 | Colab | Kaggle | Studio Lab | | :--- | :--- | :--- | :--- | | 1章 バンディット問題 | [](https://colab.research.google.com/github/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/01_bandit.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/01_bandit.ipynb) | [](https://studiolab.sagemaker.aws/import/github/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/01_bandit.ipynb) | | 4章 動的計画法 | [](https://colab.research.google.com/github/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/04_dynamic_programming.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/04_dynamic_programming.ipynb) | [](https://studiolab.sagemaker.aws/import/github/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/04_dynamic_programming.ipynb) | | 5章 モンテカルロ法 | [](https://colab.research.google.com/github/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/05_montecarlo.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/05_montecarlo.ipynb) | [](https://studiolab.sagemaker.aws/import/github/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/05_montecarlo.ipynb) | | 6章 TD法 | [](https://colab.research.google.com/github/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/06_temporal_difference.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/06_temporal_difference.ipynb) | [](https://studiolab.sagemaker.aws/import/github/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/06_temporal_difference.ipynb) | | 7章 ニューラルネットワークとQ学習 | [](https://colab.research.google.com/github/oreilly-japan/deep-learning-from-scratch-4/blob/master/notebooks/07_neural_networks.ipynb) | [ — educational materials and examples for learning deep learning.
matched fp:934111edcf246d76, llm:Repository contains code for the book 'Deep Learning from Scratch 4' (O'Reilly Japan, 2022) — educational materials and examples for learning deep learning.