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    <h1 class="post-title"><a class="post-link" href="/post/auto-sklearn-part3/">auto-sklearn代码阅读 part3</a></h1>
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      <span class="post-time"> 2019-11-05 </span>
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          <a href="/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/"> 机器学习 </a>
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      <p>auto-sklearn采用了贝叶斯优化作为超参数寻优算法。这是比较常见的黑盒优化算法，本章主要介绍这部分的原理</p>
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    <h1 class="post-title"><a class="post-link" href="/post/auto-sklearn-part2/">auto-sklearn代码阅读 part2</a></h1>
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      <span class="post-time"> 2019-11-05 </span>
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          <a href="/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/"> 机器学习 </a>
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      <p>这一章简单介绍下auto-sklearn在特征预处理过程中使用的一些算法，其实很多都还没弄明白。后续需要进行更深入的学习，以及数据预处理的方法</p>
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    <h1 class="post-title"><a class="post-link" href="/post/auto-sklearn-part1/">auto-sklearn代码阅读 part1</a></h1>
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      <span class="post-time"> 2019-10-22 </span>
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          <a href="/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/"> 机器学习 </a>
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      <p><strong>自动机器学习</strong>（<strong>AutoML</strong>）是将机器学习应用于现实问题的端到端流程自动化的过程。工作中刚好有用到auto-sklearn相关技术，记录一下代码阅读笔记。</p>
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    <h1 class="post-title"><a class="post-link" href="/post/pytorch-5-thc-part1/">Pytorch源码阅读-ch5-THC part1</a></h1>
    <div class="post-meta">
      <span class="post-time"> 2019-10-09 </span>
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          <a href="/categories/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/"> 深度学习 </a>
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      <p>这章开始是Pytorch CUDA的部分</p>
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    <h1 class="post-title"><a class="post-link" href="/post/pytorch-4-tensor%E5%B9%B6%E8%A1%8C%E8%BF%90%E7%AE%97/">Pytorch源码阅读-ch4-Tensor并行运算</a></h1>
    <div class="post-meta">
      <span class="post-time"> 2019-10-08 </span>
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          <a href="/categories/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/"> 深度学习 </a>
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      <p>这章主要包括<code>THTensor</code>是如何进行并行计算，进行性能优化的</p>
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