chapter_computational_complexity/ #532
giscus[bot]
bot
Replies: 54 comments 13 replies
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这个网站是哪个框架搭的？ |
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mkdocs material |
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插图AI生成的吗，好评 |
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是的！ |
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是mj吗？prompt是什么 |
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应该如何获得这张图片真的很喜欢 |
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右键保存～ |
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网站有书签功能吗，看到哪里总忘 |
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暂时没有哦 |
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要完成这个功能需要记录cookie吧 |
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比起「时空向导」，在学习的时候，感觉时间和空间复杂度更像是评价「算法」的两个“评价维度”，就好像我们在评价不同学生的时候，会用学习能力、道德品质、运动健康等维度进行评价。 |
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时空是两个维度，角色是“向导”。这是因为算法研究的总体目标就是降低时间与空间复杂度，实现又快又省的算法。 |
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原来如此，明白啦 k 大 |
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hao |
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Hi 派大星 |
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膜拜大佬 |
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我有一个问题是最近在学习李沐老师《动手学深度学习》中自注意力机制时有一页是用来比较CNN、RNN和self-attention的计算复杂度，我不太清楚其中处理序列数据的CNN和RNN网络的计算复杂度是如何算的，K神可以解答下吗 |
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Hi，这个书中介绍的挺详细的，在“10.6.2 比较卷积神经网络、循环神经网络和自注意力”。推荐也可以看看李沐老师的 B 站视频讲解。 |
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以上是原文。这里推算技巧就是不要考虑序列的边界，将序列中的 n 个节点都想象成一样的，那么就是直接乘起来就可以了。 |
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这里我的理解是，假定没有padding，步长为1，卷积核为ddk*1，卷积核运算的次数是n-k+1次，一般情况下n远大于k，所以这里是knd^2。不知道这样理解对不对k神 |
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打卡9 |
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打卡 |
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小王匠打卡 |
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打卡 |
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2024.1.26 mark |
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2024.02.22 mark，go for it |
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打卡 |
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2024.3.16 |
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打卡（六个表情😄❤️🚀👍🎉👁️👁️） |
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I'm comming, gogogo |
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1 |
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111 |
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打卡 |
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爱了爱了 |
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准备动手 |
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第二天打卡 |
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打卡1 |
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2025.2.20，打卡第二章！ |
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2025/2/23 打卡第二章 |
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动手！ |
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2025/4/15打卡 |
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一般不是都从数据结构数组链表这些开始的吗？怎么作者会选择以复杂度分析先开始。虽然我觉得这样挺好 |
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有种时间法则和空间法则即视感 |
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chapter_computational_complexity/
一本动画图解、能运行、可提问的数据结构与算法入门书
https://www.hello-algo.com/chapter_computational_complexity/
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