机器学习入门书单_机器学习入门书单整理

继NLP之后，我又开了ML这个大坑。这是因为NLP涉及到太多的ML模型，仅仅拿过来用的话，我实现的HanLP已经快到个人极限了。而模型背后的原理、如何优化、如何并行化等问题，都需要寻根求源才能解决。

所以我找了个书单自学，电子书为主，顺便分享出来。

  
  <ol class="linenums" style="margin:0px 0px 0px 30px; padding:0px; list-style-position:initial"><li class="L0" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pln" style="color:rgb(102,217,239)">ML</span><span class="pun" style="color:rgb(248,248,242)">书单</span></li><li class="L1" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">李航.统计学习方法.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L2" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">机器学习及其应用.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L3" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="typ" style="color:rgb(166,226,46)">All</span><span class="pln" style="color:rgb(102,217,239)"> of </span><span class="typ" style="color:rgb(166,226,46)">Statistics</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="pun" style="color:rgb(248,248,242)">-</span><span class="pln" style="color:rgb(102,217,239)"> A </span><span class="typ" style="color:rgb(166,226,46)">Concise</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Course</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="kwd" style="color:rgb(249,38,89)">in</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Statistical</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Inference</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="pun" style="color:rgb(248,248,242)">-</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Larry</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Wasserman</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="pun" style="color:rgb(248,248,242)">-</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Springer</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L4" style="margin-bottom:0px; 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padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  PRML</span><span class="pun" style="color:rgb(248,248,242)">读书会合集打印版.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L7" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="typ" style="color:rgb(166,226,46)">Programming</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Collective</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Intelligence</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L8" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">[奥莱理]</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Machine</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Learning</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="kwd" style="color:rgb(249,38,89)">for</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Hackers</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L9" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">[机器学习]</span><span class="typ" style="color:rgb(166,226,46)">Tom</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="typ" style="color:rgb(166,226,46)">Mitchell</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L0" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">《大数据：互联网大规模数据挖掘与分布式处理》迷你书.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L1" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">推荐系统实践.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L2" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">数据挖掘-实用机器学习技术（中文第二版）.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L3" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">数据挖掘</span><span class="pln" style="color:rgb(102,217,239)">_</span><span class="pun" style="color:rgb(248,248,242)">概念与技术.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L4" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">机器学习-</span><span class="typ" style="color:rgb(166,226,46)">Mitchell</span><span class="pun" style="color:rgb(248,248,242)">-中文-清晰版.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L5" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">机器学习导论.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L6" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">模式分类第二版中文版</span><span class="typ" style="color:rgb(166,226,46)">Duda</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span><span class="pun" style="color:rgb(248,248,242)">（全）.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L7" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">深入搜索引擎--海量信息的压缩、索引和查询.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L8" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">矩阵分析.美国</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="typ" style="color:rgb(166,226,46)">Roger</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="pln" style="color:rgb(102,217,239)">A</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="typ" style="color:rgb(166,226,46)">Horn</span><span class="pun" style="color:rgb(248,248,242)">.扫描版.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L9" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span><span class="pun" style="color:rgb(248,248,242)">统计学习基础</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="pun" style="color:rgb(248,248,242)">数据挖掘、推理与预测.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L0" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">  </span></li><li class="L1" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">├─机器学习实战</span></li><li class="L2" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">      machinelearninginaction</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="pln" style="color:rgb(102,217,239)">zip</span></li><li class="L3" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">      </span><span class="pun" style="color:rgb(248,248,242)">机器学习实战</span><span class="pln" style="color:rgb(102,217,239)"> </span><span class="pun" style="color:rgb(248,248,242)">单页.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L4" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">      </span><span class="pun" style="color:rgb(248,248,242)">机器学习实战.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L5" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">│</span><span class="pln" style="color:rgb(102,217,239)">      </span></li><li class="L6" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pun" style="color:rgb(248,248,242)">└─论文文集</span></li><li class="L7" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pln" style="color:rgb(102,217,239)">    </span><span class="pun" style="color:rgb(248,248,242)">└─</span><span class="pln" style="color:rgb(102,217,239)">LDA</span></li><li class="L8" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pln" style="color:rgb(102,217,239)">            LDA</span><span class="pun" style="color:rgb(248,248,242)">-</span><span class="pln" style="color:rgb(102,217,239)">wangyi</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L9" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pln" style="color:rgb(102,217,239)">            LDA</span><span class="pun" style="color:rgb(248,248,242)">数学八卦.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li><li class="L0" style="margin-bottom:0px; padding-left:12px; color:rgb(190,190,197); margin-left:0px; list-style:decimal"><span class="pln" style="color:rgb(102,217,239)">            text</span><span class="pun" style="color:rgb(248,248,242)">-</span><span class="pln" style="color:rgb(102,217,239)">est</span><span class="pun" style="color:rgb(248,248,242)">.</span><span class="pln" style="color:rgb(102,217,239)">pdf</span></li></ol>

下载地址：百度网盘。

现在正在看《统计学习方法》，边看便用Python实现。再用Matplotlib可视化，简直太完美了，比如kd树的构建算法：

以前也看过《机器学习实战》，不过感觉偏应用，原理没讲清楚，所以中断了。再往前面看过的《智能Web算法》也是偏应用的，过了一遍之后收获也不大。至于一些兜售“XX学习班”的博客，也就采集网上零落的博文，贴一些公式和理论甚至是戏说的程度。大部分博主都挑自己擅长的讲，挑自己容易找到的抄，这样导致网上公开的都是些千篇一律的浅显东西，只能看着玩，当不得真。至于代码，更不用想了。

感觉要入门，还是得从业界经典入门，那些“实战XXX”的书只能画个葫芦，然后读者只能画个瓢。

不是说网上大部分的机器学习教程都是这样的吗：

所以说还是得从原理开始打基础吧。

上面的书单是我这个外行搜集大家推荐次数比较多的书凑起来的，只是个人书单，不保证质量。这个书单应该会不断补充（话说回来，要是能都看完估计也很了得了），如果路过的各路高人有任何建议的话，恳请留言指点迷津。

使用电子书的形式是因为，个人偏好。即使我买了实体书，一旦找到了电子书，我马上就会把纸质书扔到床底下。如果侵犯了任何人的权益，烦请及时通知。

至于何时填完这些坑，生命不息，奋斗不止吧。

网址：http://www.hankcs.com/ml/machine-learning-entry-list.html