小小学员
Little Learner
Daniel P. Friedman、Anurag Mendhekar · 初版 2023 年
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为什么值得读
- 仅需掌握几个核心语法即可动手实践完成全书
- 展示Scheme在处理矩阵与抽象概念上的表达力
- 为Lisp爱好者进入神经网络与深度学习提供阶梯
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Little Learner
Daniel P. Friedman、Anurag Mendhekar · 初版 2023 年
正在加载完整评论……
看见 Lisp 我就点赞 ;) 感兴趣的朋友，Daniel Friedman 和 Anurag Mendhekar 写过一本叫《The Little Learner》的书：https://www.thelittlelearner.com/
I see Lisp I upvote ;) For the curious, Daniel Friedman and Anurag Mendhekar wrote a book called “The Little Learner”: https://www.thelittlelearner.com/
我一直在用 Racket 刷《The Little Learner》[1]，体验非常棒。搞定这本书只需要极少量的 Racket 语法（lambda、let、define、map；差不多就这些了）。不过我顺便拓展了一下，去了解了更多关于这门语言和标准……
I've been using Racket to work through The Little Learner[1] and it's been a good experience. You need minimal Racket to work through the book (lambda, let, define, map; I think that's about it). But I branched out to learn more about the language and the standard…
……然而，只有在你拥有了一个扎实的矩阵处理接口之后，这才有意义。如果你想体会一下其中的区别，我建议翻一翻那本令人惊喜的神作《The Little Learner》。我觉得你会发现，虽然它确实展示了 Scheme（这里其实是 Racket）在自身擅长领域的强大威力，但你绝对不会想把书里的框架用于 toy 之外的任何……
…However, this is only important once you have a solid interface for working with matrices. If you want to get a feel for the difference I would suggest reading through the surprisingly excellent The Little Learner. I think you'll find that while it really demonstrates the power of Scheme (Racket in this case) in areas where it excels, you wouldn't want to use the framework in that book for anything other than toy…
我也附议。考虑到你的背景（Lisper），或许可以在《The Little Learner》出版后刷一遍这本书，再配合 Karpathy 的视频系列。接着尝试在你感兴趣的领域（文本、图像、视频、时间序列）写个稍微复杂一点的应用。另外根据我的经验给你句忠告……
I second this. Given your background (lisper) maybe do the Little Learner book once it is out + Karpathy's video series. Follow it up by building a slightly complicated application in your favourite domain (text, images, videos, time series). Also word of advise from my experience…
我最近读了《The Little Learner》，惊讶地发现仅仅因为懂 APL/J，我就已经掌握了里面的很多概念。只要有合适的库，这些向量语言拿来做神经网络/深度学习任务简直再完美不过了。
I have recently read "The Little Learner" and was quite amazed how much I knew already just because I know APL/J. With the right libraries, these vector languages would be perfect for neural network / deep learning tasks.
《The Little Learner》[0]：用 Scheme 学习基础。这是最底层的本质；没有现成框架，只有 Scheme 和函数。学完这个你就可以进阶到任何方向。接着去看《Neural Networks: Zero to Hero》[1] 搞懂 autograd 是怎么运作的，……
The Little Learner[0]: Learn the basics using scheme. This is fundamental; no frameworks, just Scheme and functions. From here you can go anywhere. Then watch Neural Networks: Zero to Hero[1] to learn how autograd works,…