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喜欢这些视频吗？考虑分享一两个。 帮助资助未来的项目：https://www.patreon.com/3blue1brown 特别感谢这些支持者：http://3b1b.co/nn2-thanks 本系列的书面/互动形式：https://www.3blue1brown.com/topics/neural-networks 该视频得到了 Amplify Partners 的支持。 对于任何早期 ML 初创公司创始人，Amplify Partners 很乐意通过 [email protected] 听取您的意见 要了解更多信息，我强烈推荐迈克尔·尼尔森的书 http://neuralnetworksanddeeplearning.com/ 本书逐步介绍了这些视频中示例背后的代码，您可以在此处找到： https://github.com/mnielsen/neural-networks-and-deep-learning MNIST 数据库： http://yann.lecun.com/exdb/mnist/ 另请查看 Chris Olah 的博客： http://colah.github.io/ 他关于神经网络和拓扑的文章特别漂亮，但说实话，那里的所有内容都很棒。 如果您喜欢，您一定会*喜欢* distill 的出版物： https://distill.pub/ 如需更多视频，Welch Labs 还提供了一些有关机器学习的精彩系列： https://youtu.be/i8D90DkCLhI https://youtu.be/bxe2T-V8XRs “但我已经如饥似渴地阅读了尼尔森、奥拉和韦尔奇的作品”，我听到你说。好吧好吧，那就看看你吧。既然如此，我可能会建议您继续阅读 Goodfellow、Bengio 和 Courville 所著的《深度学习》一书。 感谢 Lisha Li (@lishali88) 在最后的贡献，也感谢她让我对这些材料进行了如此多的思考。以下是她最后引用的文章： https://arxiv.org/abs/1611.03530 https://arxiv.org/abs/1706.05394 https://arxiv.org/abs/1412.0233 文森特·鲁宾内蒂的音乐： https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
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