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Hello 算法
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1.1. 算法无处不在
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0. 写在前面
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0. 写在前面
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0.1. 关于本书
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0.2. 如何使用本书
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0.3. 编程环境安装
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0.4. 一起参与创作
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1. 引言
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1. 引言
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1.1. 算法无处不在
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1.2. 算法是什么
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1.3. 小结
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2. 计算复杂度
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2. 计算复杂度
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2.1. 算法效率评估
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2.2. 时间复杂度
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2.3. 空间复杂度
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2.4. 权衡时间与空间
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2.5. 小结
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3. 数据结构简介
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3. 数据结构简介
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3.3. 小结
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4. 数组与链表
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6. 散列表
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6. 散列表
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6.1. 哈希表（ ）
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6.2. 哈希冲突处理
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6.3. 小结
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7. 二叉树
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7. 二叉树
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7.4. AVL 树 *
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7.5. 小结
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8. 堆
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8. 堆
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8.1. 堆（ ）
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9. 图
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9. 图
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9.1. 图（ ）
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9.2. 图基础操作
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9.3. 图的遍历
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9.4. 小结
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10. 查找算法
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10. 查找算法
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10.1. 线性查找
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10.2. 二分查找
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10.3. 哈希查找
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10.4. 小结
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11. 排序算法
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11. 排序算法
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11.4. 快速排序
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< h1 id = "11" > 1.1. 算法无处不在< a class = "headerlink" href = "#11" title = "Permanent link" > ¶ < / a > < / h1 >
< p > 听到“算法”这个词，我们一般会联想到数学。但实际上，大多数算法并不包含复杂的数学，而更像是在考察基本逻辑，而这些逻辑在我们日常生活中处处可见。< / p >
< p > 在正式介绍算法之前，我想告诉你一件有趣的事：< strong > 其实，你在过去已经学会了很多算法，并且已经习惯将它们应用到日常生活中< / strong > 。接下来，我将介绍两个具体例子来佐证。< / p >
< p > < strong > 例一：拼积木< / strong > 。一套积木，除了有许多部件之外，还会附送详细的拼装说明书。我们按照说明书上一步步操作，即可拼出复杂的积木模型。< / p >
< p > 如果从数据结构与算法的角度看，大大小小的「积木」就是数据结构，而「拼装说明书」上的一系列步骤就是算法。< / p >
< p > < strong > 例二：查字典< / strong > 。在字典中，每个汉字都有一个对应的拼音，而字典是按照拼音的英文字母表顺序排列的。假设需要在字典中查询任意一个拼音首字母为 < span class = "arithmatex" > \(r\)< / span > 的字，一般我们会这样做：< / p >
< ol >
< li > 打开字典大致一半页数的位置，查看此页的首字母是什么（假设为 < span class = "arithmatex" > \(m\)< / span > ） ； < / li >
< li > 由于在英文字母表中 < span class = "arithmatex" > \(r\)< / span > 在 < span class = "arithmatex" > \(m\)< / span > 的后面，因此应排除字典前半部分，查找范围仅剩后半部分；< / li >
< li > 循环执行步骤 1-2 ，直到找到拼音首字母为 < span class = "arithmatex" > \(r\)< / span > 的页码时终止。< / li >
< / ol >
< div class = "tabbed-set tabbed-alternate" data-tabs = "1:5" > < input checked = "checked" id = "__tabbed_1_1" name = "__tabbed_1" type = "radio" / > < input id = "__tabbed_1_2" name = "__tabbed_1" type = "radio" / > < input id = "__tabbed_1_3" name = "__tabbed_1" type = "radio" / > < input id = "__tabbed_1_4" name = "__tabbed_1" type = "radio" / > < input id = "__tabbed_1_5" name = "__tabbed_1" type = "radio" / > < div class = "tabbed-labels" > < label for = "__tabbed_1_1" > < 1> < / label > < label for = "__tabbed_1_2" > < 2> < / label > < label for = "__tabbed_1_3" > < 3> < / label > < label for = "__tabbed_1_4" > < 4> < / label > < label for = "__tabbed_1_5" > < 5> < / label > < / div >
< div class = "tabbed-content" >
< div class = "tabbed-block" >
< p > < img alt = "查字典步骤" src = "../algorithms_are_everywhere.assets/look_up_dictionary_step_1.png" / > < / p >
< / div >
< div class = "tabbed-block" >
< p > < img alt = "look_up_dictionary_step_2" src = "../algorithms_are_everywhere.assets/look_up_dictionary_step_2.png" / > < / p >
< / div >
< div class = "tabbed-block" >
< p > < img alt = "look_up_dictionary_step_3" src = "../algorithms_are_everywhere.assets/look_up_dictionary_step_3.png" / > < / p >
< / div >
< div class = "tabbed-block" >
< p > < img alt = "look_up_dictionary_step_4" src = "../algorithms_are_everywhere.assets/look_up_dictionary_step_4.png" / > < / p >
< / div >
< div class = "tabbed-block" >
< p > < img alt = "look_up_dictionary_step_5" src = "../algorithms_are_everywhere.assets/look_up_dictionary_step_5.png" / > < / p >
< / div >
< / div >
< / div >
< p > 查字典这个小学生的标配技能，实际上就是大名鼎鼎的「二分查找」。从数据结构角度，我们可以将字典看作是一个已排序的「数组」；而从算法角度，我们可将上述查字典的一系列指令看作是「二分查找」算法。< / p >
< p > 小到烹饪一道菜、大到星际航行，几乎所有问题的解决都离不开算法。计算机的出现，使我们可以通过编程将数据结构存储在内存中，也可以编写代码来调用 CPU, GPU 执行算法，从而将生活中的问题搬运到计算机中，更加高效地解决各式各样的复杂问题。< / p >
< div class = "admonition tip" >
< p class = "admonition-title" > Tip< / p >
< p > 读到这里，如果你感到对数据结构、算法、数组、二分查找等此类概念一知半解，那么就太好了！因为这正是本书存在的价值，接下来，本书将会一步步地引导你进入数据结构与算法的知识殿堂。< / p >
< / div >
< h2 id = "__comments" > 评论< / h2 >
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