《动手学深度学习》

《动手学深度学习》

第二版预览版

跳转第一版

面向中文读者的能运行、可讨论的深度学习教科书

含 NumPy/MXNet、PyTorch 和 TensorFlow 实现

被全球 55 个国家 300 所大学用于教学

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• 【关注第二版更新】 英文版已翻译至中文版第二版，并含多种深度学习框架的实现。 英文版还新增了推荐系统和深度学习的数学等。 如果想及时获取最新修订或增添的信息， 请关注本书的中文开源项目和英文开源项目。
• 【购买第一版纸质书（上架4周重印2次，累计3万+册）】 纸质书在内容上与在线版大致相同，但力求在样式、术语标注、语言表述、用词规范、标点以及图、表、章节的索引上符合出版标准和学术规范。 可以在 京东、 当当、 天猫 购买全彩精装版； 或者在 京东、 当当、 天猫 购买黑白平装版。 [新书榜] [关于样书]
• 【免费资源（新增中文版课件）】 在校学生和老师可以申请用于本书学习或教学的免费计算资源。 课件、作业、教学视频等资源可参考伯克利“深度学习导论” 课程大纲 中的链接（中文版课件）。 基于本书较早草稿内容的中文教学视频在： B站 和 Youtube。 [关于资源]

作者

阿斯顿·张

亚马逊高级科学家

扎卡里 C. 立顿

亚马逊科学家，美国卡内基梅隆大学助理教授

李沐

亚马逊资深首席科学家

亚历山大 J. 斯莫拉

亚马逊副总裁/杰出科学家

第二卷章节作者

布伦特 沃尼斯

亚马逊高级科学家

深度学习的数学

瑞潮儿·胡

亚马逊科学家

深度学习的数学

张帅

苏黎世联邦理工学院博士后

推荐系统

郑毅

谷歌科学家

推荐系统

框架改编者

阿尼如 达格

印度理工学院罗克分校

PyTorch改编

唐源

蚂蚁集团高级工程师

TensorFlow改编

中文版译者

何孝霆

亚马逊解决方案架构师

瑞潮儿·胡

亚马逊科学家

感谢来自社区的 100+ 位贡献者

为本书贡献

每一小节都是可以运行的 Jupyter 记事本

你可以自由修改代码和超参数来获取及时反馈，从而积累深度学习的实战经验。

本地运行 [ 亚马逊 SageMaker

Studio Lab ](https://studiolab.sagemaker.aws/import/github/d2l-ai/d2l-pytorch-sagemaker-studio-lab/blob/main/GettingStarted-D2L.ipynb)

[ 亚马逊

SageMaker ](https://d2l.ai/chapter_appendix-tools-for-deep-learning/sagemaker.html)

[ 谷歌

Colab ](https://d2l.ai/chapter_appendix-tools-for-deep-learning/colab.html)

公式 + 图示 + 代码

我们不仅结合文字、公式和图示来阐明深度学习里常用的模型和算法，还提供代码来演示如何从零开始实现它们，并使用真实数据来提供一个交互式的学习体验。

活跃社区支持

你可以通过每个章节最后的链接来同社区的数千名小伙伴一起讨论学习。

本书（中英文版）被用作教材或参考书

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英文版引用

@article{zhang2021dive,
    title={Dive into Deep Learning},
    author={Zhang, Aston and Lipton, Zachary C. and Li, Mu and Smola, Alexander J.},
    journal={arXiv preprint arXiv:2106.11342},
    year={2021}
}

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