Deployed bad66aa with MkDocs version: 1.4.2

changelog/index.html

@@ -1034,6 +1034,7 @@ <h1 id="changelog">Changelog<a class="headerlink" href="#changelog" title="Perma
 <div class="heti-skip">
 <h2 id="2025">2025 年<a class="headerlink" href="#2025" title="Permanent link">¶</a></h2>
 <ul>
+<li><span style="font-family: var(--md-code-font-family)">01-10 <a href="https://github.com/ZJU-Turing/TuringCourses/commit/bad66aa456da1e9df12eb696036403a92a1fab0f">bad66aa</a> </span>docs: 更新<a href="https://zju-turing.github.io/TuringCourses/major_elective/ai_logic/">人工智能逻辑</a>和<a href="https://zju-turing.github.io/TuringCourses/major_mandatory/machine_learning/">机器学习</a>相关内容，新增<a href="https://zju-turing.github.io/TuringCourses/major_elective/brain_inspired_ai/">脑启发人工智能导论</a>内容 (<a href="https://github.com/ZJU-Turing/TuringCourses/pull/209">#209</a>)</li>
 <li><span style="font-family: var(--md-code-font-family)">01-10 <a href="https://github.com/ZJU-Turing/TuringCourses/commit/2905b27f5e828758e0f3ed5264728357fa42a396">2905b27</a> </span>docs: 更新<a href="https://zju-turing.github.io/TuringCourses/major_mandatory/computer_vision/">计算机视觉导论</a>相关内容，新增<a href="https://zju-turing.github.io/TuringCourses/major_elective/computer_graphics/">计算机图形学</a>内容 (<a href="https://github.com/ZJU-Turing/TuringCourses/pull/208">#208</a>)<ul>
 <li>🔗 <a href="https://zju-turing.github.io/TuringCourses/short_term/llm_practice/">大模型应用与实践</a> </li>
 </ul>

major_elective/ai_logic/index.html

@@ -1049,7 +1049,7 @@
 <svg viewbox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"></path></svg>
 </a>
 <div class="admonition warning">
-<p class="admonition-title">1720719966</p>
+<p class="admonition-title">1736517728</p>
 </div>
 <h1 id="_1">人工智能逻辑<a class="headerlink" href="#_1" title="Permanent link"><span><span class="heti-spacing"> </span>¶</span></a></h1>
 <div class="badges">
@@ -1101,7 +1101,7 @@ <h2 id="_7">分数构成<a class="headerlink" href="#_7" title="Permanent link">
 <li>
 <p>作业（25%）</p>
 <p><span>21:<span class="heti-spacing"> </span></span>每周都会布置思考题，设置的<span class="heti-skip"><span class="heti-spacing"> </span>ddl<span class="heti-spacing"> </span></span>一般是下周上课前，每次题目的数量在<span class="heti-skip"><span class="heti-spacing"> </span>4-6<span class="heti-spacing"> </span></span>题不等。一般情况思考题就是教材的课后习题。由于教材尚未出版，这个方向也相对小众，作业很难找到现成的答案，作业的难度也参差不齐，快的时候一小时可以搞定，但在比较难的章节可能需要花接近半天的时间。</p>
-<p><span>22:<span class="heti-spacing"> </span></span>每周会有思考题，但今年助教姐姐很好，基本每周最多只有<span class="heti-skip"><span class="heti-spacing"> </span>3<span class="heti-spacing"> </span></span>道，很多时候只有<span class="heti-skip"><span class="heti-spacing"> </span>1<span class="heti-spacing"> </span></span>道，也是来自课后习题，有的简单也有的有一定难度，没有答案和反馈。</p>
+<p><span>22:<span class="heti-spacing"> </span></span>每周会有思考题，但今年助教姐姐很好，基本每周最多只有<span class="heti-skip"><span class="heti-spacing"> </span>3<span class="heti-spacing"> </span></span>道，很多时候只有<span class="heti-skip"><span class="heti-spacing"> </span>1<span class="heti-spacing"> </span></span>道，也是来自课后习题，有的简单也有的有一定难度，没有答案和反馈。<span>22<span class="heti-spacing"> </span></span>年的作业我附在了<a href="https://github.com/dieKarotte/AI_Logic">这里</a>，有需要的同学可以参考一下，请不要进行任何形式的抄袭。</p>
 </li>
 <li>
 <p>考试（60%）</p>
@@ -1143,7 +1143,7 @@ <h2 id="_7">分数构成<a class="headerlink" href="#_7" title="Permanent link">
 }
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 <div id="footer-wrapper">
-<p><span class="twemoji"><svg viewbox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path d="M21 13.1c-.1 0-.3.1-.4.2l-1 1 2.1 2.1 1-1c.2-.2.2-.6 0-.8l-1.3-1.3c-.1-.1-.2-.2-.4-.2m-1.9 1.8-6.1 6V23h2.1l6.1-6.1-2.1-2M12.5 7v5.2l4 2.4-1 1L11 13V7h1.5M11 21.9c-5.1-.5-9-4.8-9-9.9C2 6.5 6.5 2 12 2c5.3 0 9.6 4.1 10 9.3-.3-.1-.6-.2-1-.2s-.7.1-1 .2C19.6 7.2 16.2 4 12 4c-4.4 0-8 3.6-8 8 0 4.1 3.1 7.5 7.1 7.9l-.1.2v1.8Z"></path></svg></span> 2024-07-12  <span class="twemoji"><svg viewbox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path d="M12 .297c-6.63 0-12 5.373-12 12 0 5.303 3.438 9.8 8.205 11.385.6.113.82-.258.82-.577 0-.285-.01-1.04-.015-2.04-3.338.724-4.042-1.61-4.042-1.61C4.422 18.07 3.633 17.7 3.633 17.7c-1.087-.744.084-.729.084-.729 1.205.084 1.838 1.236 1.838 1.236 1.07 1.835 2.809 1.305 3.495.998.108-.776.417-1.305.76-1.605-2.665-.3-5.466-1.332-5.466-5.93 0-1.31.465-2.38 1.235-3.22-.135-.303-.54-1.523.105-3.176 0 0 1.005-.322 3.3 1.23.96-.267 1.98-.399 3-.405 1.02.006 2.04.138 3 .405 2.28-1.552 3.285-1.23 3.285-1.23.645 1.653.24 2.873.12 3.176.765.84 1.23 1.91 1.23 3.22 0 4.61-2.805 5.625-5.475 5.92.42.36.81 1.096.81 2.22 0 1.606-.015 2.896-.015 3.286 0 .315.21.69.825.57C20.565 22.092 24 17.592 24 12.297c0-6.627-5.373-12-12-12"></path></svg></span> Contributors <span class="contributors"><a href="https://github.com/dieKarotte" target="_blank" title="dieKarotte"><img alt="dieKarotte" src="https://avatars.githubusercontent.com/u/140470605"/></a><a href="https://github.com/TonyCrane" target="_blank" title="TonyCrane"><img alt="TonyCrane" src="https://avatars.githubusercontent.com/u/44120331"/></a><a href="https://github.com/DaViD-Pigeon" target="_blank" title="DaViD-Pigeon"><img alt="DaViD-Pigeon" src="https://avatars.githubusercontent.com/u/117525184"/></a></span></p>
+<p><span class="twemoji"><svg viewbox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path d="M21 13.1c-.1 0-.3.1-.4.2l-1 1 2.1 2.1 1-1c.2-.2.2-.6 0-.8l-1.3-1.3c-.1-.1-.2-.2-.4-.2m-1.9 1.8-6.1 6V23h2.1l6.1-6.1-2.1-2M12.5 7v5.2l4 2.4-1 1L11 13V7h1.5M11 21.9c-5.1-.5-9-4.8-9-9.9C2 6.5 6.5 2 12 2c5.3 0 9.6 4.1 10 9.3-.3-.1-.6-.2-1-.2s-.7.1-1 .2C19.6 7.2 16.2 4 12 4c-4.4 0-8 3.6-8 8 0 4.1 3.1 7.5 7.1 7.9l-.1.2v1.8Z"></path></svg></span> 2025-01-10  <span class="twemoji"><svg viewbox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path d="M12 .297c-6.63 0-12 5.373-12 12 0 5.303 3.438 9.8 8.205 11.385.6.113.82-.258.82-.577 0-.285-.01-1.04-.015-2.04-3.338.724-4.042-1.61-4.042-1.61C4.422 18.07 3.633 17.7 3.633 17.7c-1.087-.744.084-.729.084-.729 1.205.084 1.838 1.236 1.838 1.236 1.07 1.835 2.809 1.305 3.495.998.108-.776.417-1.305.76-1.605-2.665-.3-5.466-1.332-5.466-5.93 0-1.31.465-2.38 1.235-3.22-.135-.303-.54-1.523.105-3.176 0 0 1.005-.322 3.3 1.23.96-.267 1.98-.399 3-.405 1.02.006 2.04.138 3 .405 2.28-1.552 3.285-1.23 3.285-1.23.645 1.653.24 2.873.12 3.176.765.84 1.23 1.91 1.23 3.22 0 4.61-2.805 5.625-5.475 5.92.42.36.81 1.096.81 2.22 0 1.606-.015 2.896-.015 3.286 0 .315.21.69.825.57C20.565 22.092 24 17.592 24 12.297c0-6.627-5.373-12-12-12"></path></svg></span> Contributors <span class="contributors"><a href="https://github.com/dieKarotte" target="_blank" title="dieKarotte"><img alt="dieKarotte" src="https://avatars.githubusercontent.com/u/140470605"/></a><a href="https://github.com/TonyCrane" target="_blank" title="TonyCrane"><img alt="TonyCrane" src="https://avatars.githubusercontent.com/u/44120331"/></a><a href="https://github.com/DaViD-Pigeon" target="_blank" title="DaViD-Pigeon"><img alt="DaViD-Pigeon" src="https://avatars.githubusercontent.com/u/117525184"/></a></span></p>
 </div>
 <style>
 .md-content .admonition:first-of-type {

major_elective/brain_inspired_ai/index.html

@@ -698,9 +698,55 @@
 </li>
 <li class="md-nav__item md-nav__item--active">
 <input class="md-nav__toggle md-toggle" data-md-toggle="toc" id="__toc" type="checkbox"/>
+<label class="md-nav__link md-nav__link--active" for="__toc">
+          脑启发人工智能导论
+          <span class="md-nav__icon md-icon"></span>
+</label>
 <a class="md-nav__link md-nav__link--active" href="./">
         脑启发人工智能导论
       </a>
+<nav aria-label="目录" class="md-nav md-nav--secondary">
+<label class="md-nav__title" for="__toc">
+<span class="md-nav__icon md-icon"></span>
+      目录
+    </label>
+<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix="">
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_2">
+    课程学习内容
+  </a>
+<nav aria-label="课程学习内容" class="md-nav">
+<ul class="md-nav__list">
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_3">
+    先修要求
+  </a>
+</li>
+</ul>
+</nav>
+</li>
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_4">
+    任课教师
+  </a>
+</li>
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_5">
+    课程教材
+  </a>
+</li>
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_6">
+    分数构成
+  </a>
+</li>
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_7">
+    笔者的话
+  </a>
+</li>
+</ul>
+</nav>
 </li>
 <li class="md-nav__item">
 <a class="md-nav__link" href="../ai_logic/">
@@ -953,6 +999,46 @@
 <div class="md-sidebar__scrollwrap">
 <div class="md-sidebar__inner">
 <nav aria-label="目录" class="md-nav md-nav--secondary">
+<label class="md-nav__title" for="__toc">
+<span class="md-nav__icon md-icon"></span>
+      目录
+    </label>
+<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix="">
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_2">
+    课程学习内容
+  </a>
+<nav aria-label="课程学习内容" class="md-nav">
+<ul class="md-nav__list">
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_3">
+    先修要求
+  </a>
+</li>
+</ul>
+</nav>
+</li>
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_4">
+    任课教师
+  </a>
+</li>
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_5">
+    课程教材
+  </a>
+</li>
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_6">
+    分数构成
+  </a>
+</li>
+<li class="md-nav__item">
+<a class="md-nav__link" href="#_7">
+    笔者的话
+  </a>
+</li>
+</ul>
 </nav>
 </div>
 </div>
@@ -963,7 +1049,38 @@
 <svg viewbox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"></path></svg>
 </a>
 <h1 id="_1">脑启发人工智能导论<a class="headerlink" href="#_1" title="Permanent link"><span><span class="heti-spacing"> </span>¶</span></a></h1>
-<p><span>#TODO:<span class="heti-spacing"> </span></span>目前还没有内容，待完善。</p>
+<!-- \#TODO: 目前还没有内容，待完善。 -->
+<div class="badges">
+<span class="badge ai-badge">AI 专业选修</span>
+</div>
+<h2 id="_2">课程学习内容<a class="headerlink" href="#_2" title="Permanent link"><span><span class="heti-spacing"> </span>¶</span></a></h2>
+<p>前半部分是对认知神经科学导论的无意义重复。后半部分是祁玉老师讲授的有关脑启发人工智能的内容，包括脑机、类脑计算等部分。</p>
+<h3 id="_3">先修要求<a class="headerlink" href="#_3" title="Permanent link"><span><span class="heti-spacing"> </span>¶</span></a></h3>
+<p>可以先修认知神经科学导论，但是毫无疑问的，这门课也一样<strong>不推荐选修</strong>。</p>
+<h2 id="_4">任课教师<a class="headerlink" href="#_4" title="Permanent link"><span><span class="heti-spacing"> </span>¶</span></a></h2>
+<p>本课程由唐华锦老师和祁玉老师共同授课。</p>
+<p>唐华锦老师：<!-- 我拒绝评价。 --></p>
+<p>祁玉老师：讲授是清晰的、明确的，并且会有实例来帮助同学理解。</p>
+<p>同时唐华锦老师会请他的博士生来为大家讲授<span class="heti-skip"><span class="heti-spacing"> </span>SPAIC<span class="heti-spacing"> </span></span>平台的相关知识，就像在认知神经科学导论课程上的那样。还会有一些实验室的博士生来讲授一些实验室的前沿研究内容，几位博士生的水平都是很高的，可以清晰、自信的介绍自己的研究方向，也会有一些实验室的展示，对于<span class="heti-skip"><span class="heti-spacing"> </span>SNN<span class="heti-spacing"> </span></span>和类脑计算感兴趣的同学可以进行了解。</p>
+<h2 id="_5">课程教材<a class="headerlink" href="#_5" title="Permanent link"><span><span class="heti-spacing"> </span>¶</span></a></h2>
+<p>无</p>
+<h2 id="_6">分数构成<a class="headerlink" href="#_6" title="Permanent link"><span><span class="heti-spacing"> </span>¶</span></a></h2>
+<p>和认知神经科学导论一样，这门课的分数是非公开的，但是可以确定的是，这门课的分数和你的预期会存在一定的差距。</p>
+<p>本课程的考核内容如下：</p>
+<ul>
+<li>一篇神经科学论文的阅读展示：和认知神经科学导论一样，这门课程的考核方式是阅读一篇神经科学论文，并进行展示。甚至连论文的名录都大有重叠，要是你手速够快抢得到之前讲过的那篇，那么说不定你会收获和之前一样的分数。值得一提的是，如果你选择在第一周展示，因为你的展示准备时间“比别人短”，你会获得额外的加分。</li>
+</ul>
+<!-- 众所周知的是，少有同学因为兴趣来上这门课，因此稀稀落落的同学并没有人在听，老师也不是特别在意。 -->
+<ul>
+<li>
+<p>课堂签到：本学期一共进行了<span class="heti-skip"><span class="heti-spacing"> </span>3<span class="heti-spacing"> </span></span>次线下的纸质签到，看不出占比，并且大家自觉的签完就走，老师也不追问。</p>
+</li>
+<li>
+<p>project：单人完成，平台是唐华锦老师实验室开发的<span class="heti-skip"><span class="heti-spacing"> </span>SPAIC<span class="heti-spacing"> </span></span>平台。今年有<span class="heti-skip"><span class="heti-spacing"> </span>4<span class="heti-spacing"> </span></span>块内容，分别是<span class="heti-skip"><span class="heti-spacing"> </span>LIF<span class="heti-spacing"> </span></span>和<span class="heti-skip"><span class="heti-spacing"> </span>GLIF<span class="heti-spacing"> </span></span>神经元模型（30%+30%）、<span>STCA<span class="heti-spacing"> </span></span>算法<span class="heti-skip"><span class="heti-spacing"> </span>MNIST<span class="heti-spacing"> </span></span>分类（30%）、复现<span class="heti-skip"><span class="heti-spacing"> </span>23<span class="heti-spacing"> </span></span>年唐中的一篇<span class="heti-skip"><span class="heti-spacing"> </span>ICML<span class="heti-spacing"> </span></span>里面的梯度替代算法<span><span class="heti-spacing"> </span>(10%)</span>，并且要求在最后一节课上每人进行展示。在之前的课上这部分内容有发过<span><span class="heti-spacing"> </span>ppt</span>，因此除了最后一个任务之外，都可以参考<span class="heti-skip"><span class="heti-spacing"> </span>demo<span class="heti-spacing"> </span></span>代码进行完成。考虑到这些任务根本做不出什么区别，所以每人<span class="heti-skip"><span class="heti-spacing"> </span>5<span class="heti-spacing"> </span></span>分钟的展示就好像是一个大型的复制粘贴现场，笔者也不知道这个展示的意义何在，想必给出的分数也是不言自明的。</p>
+</li>
+</ul>
+<h2 id="_7">笔者的话<a class="headerlink" href="#_7" title="Permanent link"><span><span class="heti-spacing"> </span>¶</span></a></h2>
+<p>不推荐选修该课程，原因是自明的。</p>
 <hr/>
 <style>
 #footer-wrapper {
@@ -993,7 +1110,7 @@ <h1 id="_1">脑启发人工智能导论<a class="headerlink" href="#_1" title="P
 }
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