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chapter_preface/suggestions/index.html
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<p>从总体上看，我们可以将学习数据结构与算法的过程划分为三个阶段。</p> <p>从总体上看，我们可以将学习数据结构与算法的过程划分为三个阶段。</p>
<ol> <ol>
<li><strong>算法入门</strong>。我们需要熟悉各种数据结构的特点和用法，学习不同算法的原理、流程、用途和效率等方面内容。</li> <li><strong>算法入门</strong>。我们需要熟悉各种数据结构的特点和用法，学习不同算法的原理、流程、用途和效率等方面内容。</li>
<li><strong>刷算法题</strong>。建议从热门题目开刷，如<a href="https://leetcode.cn/problem-list/xb9nqhhg/">剑指 Offer</a>和<a href="https://leetcode.cn/problem-list/2cktkvj/">LeetCode Hot 100</a>，先积累至少 100 道题目，熟悉主流的算法问题。初次刷题时，“知识遗忘”可能是一个挑战，但请放心，这是很正常的。我们可以按照“艾宾浩斯遗忘曲线”来复习题目，通常在进行 3-5 轮的重复后，就能将其牢记在心。</li> <li><strong>刷算法题</strong>。建议从热门题目开刷，如<a href="https://leetcode.cn/studyplan/coding-interviews/">剑指 Offer</a>和<a href="https://leetcode.cn/studyplan/top-100-liked/">LeetCode Hot 100</a>，先积累至少 100 道题目，熟悉主流的算法问题。初次刷题时，“知识遗忘”可能是一个挑战，但请放心，这是很正常的。我们可以按照“艾宾浩斯遗忘曲线”来复习题目，通常在进行 3-5 轮的重复后，就能将其牢记在心。</li>
<li><strong>搭建知识体系</strong>。在学习方面，我们可以阅读算法专栏文章、解题框架和算法教材，以不断丰富知识体系。在刷题方面，可以尝试采用进阶刷题策略，如按专题分类、一题多解、一解多题等，相关的刷题心得可以在各个社区找到。</li> <li><strong>搭建知识体系</strong>。在学习方面，我们可以阅读算法专栏文章、解题框架和算法教材，以不断丰富知识体系。在刷题方面，可以尝试采用进阶刷题策略，如按专题分类、一题多解、一解多题等，相关的刷题心得可以在各个社区找到。</li>
</ol> </ol>
<p>如图 0-7 所示，本书内容主要涵盖“第一阶段”，旨在帮助你更高效地展开第二和第三阶段的学习。</p> <p>如图 0-7 所示，本书内容主要涵盖“第一阶段”，旨在帮助你更高效地展开第二和第三阶段的学习。</p>

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