先判断自己缺的是哪一块
机器学习岗的面试，挂人往往不是挂在「模型不会训」，而是挂在几个很具体的地方：被问到偏差方差怎么权衡，只能背出「高偏差欠拟合、高方差过拟合」；让推导逻辑回归的损失函数，写到一半卡在极大似然；手撕代码环节遇到数组或链表题，思路有但边界写不对。这三类缺口对应的是三种不同的能力，补法也不一样。
这份第四期的资料，结构上就是冲着这三类缺口去的：100 道机器学习面试题覆盖概念与推导，LeetCode 部分覆盖手撕代码，另外配有源码资料供你对照实现。它不是一份「看完就会」的读物，而是一份可以拿来测出自己漏洞的题库。下面按缺口拆开说，你可以直接跳到对应的那一节。
概念题：区分「听过」和「讲得清」
机器学习面试题里，真正拉开差距的不是定义题，而是「为什么」和「如果……会怎样」。比如正则化，很多人能说出 L1 稀疏、L2 平滑，但被追问「为什么 L1 更容易产生稀疏解」时，需要从几何角度（菱形约束的顶点落在坐标轴上）或者次梯度角度讲清楚。再比如评估指标，AUC 的物理含义、它和准确率在类别不平衡时为何结论不同，这类问题答不上来，面试官基本会判定你只调过包。
这 100 题的价值在于，它把散落在各个章节的知识点拉成了一条线：从线性模型到树模型，从损失函数到优化方法，从特征工程到模型评估。建议的用法不是顺序刷，而是先自己口头答一遍，答不顺的标记出来，再去翻对应的笔记或教材。标记出来的那些，才是你真正的复习清单。
推导题：能不能在白板上从零写出来
比概念题更进一步的，是推导。逻辑回归的对数似然、SVM 的拉格朗日对偶、EM 算法的 E 步和 M 步、反向传播的链式求导，这些在面试里常被要求「现场推一下」。这里的难点不在于公式本身，而在于你能否在没有人提示的情况下，从目标函数一步步走到更新公式，并且说清每一步在做什么。
如果推导经常卡壳，问题多半出在数学基础上——矩阵求导、凸优化、概率论的贝叶斯公式。这部分没什么捷径，只能动手抄一遍、默一遍。资料里的源码可以配合使用：把公式和对应的实现代码对着看，比只看公式更容易记住每个符号指代什么。
手撕代码：LeetCode 在 ML 面试里考什么
机器学习岗的代码环节和纯后端岗位不完全一样。除了常规的数组、字符串、链表、动态规划，还常出现两类题：一类是「用 NumPy 实现某个操作」，比如手写 softmax、K-means、卷积；另一类是把某个算法思想落到代码上，比如实现一个简单的决策树分裂。
LeetCode 部分的作用是保证你常规题的熟练度不掉链子——面试时紧张，平时写顺的题都可能出边界错误。而源码资料里如果有算法实现，值得逐行读一遍，重点看人家怎么处理数值稳定性（比如 softmax 减最大值）、怎么组织向量化运算。这些细节在面试里是加分项。
看完应该能回答的问题
- 为什么 L1 正则化能产生稀疏解，而 L2 不能？
- 逻辑回归的损失函数是怎么从极大似然推出来的？
- 类别极不平衡时，为什么准确率会骗人，该看哪些指标？
- SVM 的对偶问题解决了什么原始问题不好处理的地方？
- 手写 softmax 时，为什么要先减去输入的最大值？
- Bagging 和 Boosting 在偏差方差上的作用有什么不同？
这些问题如果你现在就能流畅回答，这门课你可以跳过大部分；如果有三四个答不上来，就按上面说的，先从标记错题开始，别从头到尾通读。查漏补缺的关键是知道自己漏在哪，而不是把资料翻完。
深度视角 | 100个机器学习面试题+LeetCode实战 - 算法面试课程 - 第四期 - 附源码资料
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? ? 04????PDF??????
? ? 01?????
????????.pdf [2.2 MB]
??????.pdf [2.9 MB]
????????.pdf [2.9 MB]
??????.pdf [793.7 KB]
??????.pdf [2.5 MB]
? ? 03??????
? ? hmm
? ? ??????
2.HMM????????????.pdf [533.8 KB]
3.HMM????????????????.pdf [547.5 KB]
4.HMM??????????.pdf [426.8 KB]
1.HMM-????????.pdf [483.7 KB]
? ? crf
? ? ??????
CRF??????.pdf [792.6 KB]
klinger-crf-intro.pdf [916.4 KB]
? ? kmeans
k-means.pdf [1.3 MB]
? ? 04??????
? ? ????
??????????????????.pdf [2.8 MB]
????????????????????.pdf [3.0 MB]
? ? ???
BFS??DFS.pdf [2.9 MB]
??????????.pdf [2.0 MB]
???????.pdf [2.9 MB]
? ? ????
?????.pptx [16.5 MB]
? ????.pptx [16.4 MB]
???????????????.pptx [16.5 MB]
kmp.pptx [17.0 MB]
513 ???????????.pptx [16.4 MB]
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??I???.pptx [16.5 MB]
69. x ???????.pptx [16.4 MB]
? ? 02?????
? ? svm
???????cs229_smo.pdf [77.8 KB]
SVM??????.pdf [1023.7 KB]
SMO????????.pdf [556.6 KB]
? ? 05??????
? ? ??????
3. leetcode416??01?????????.pdf [954.1 KB]
2. 01????????.pdf [809.4 KB]
5. ????????????(leetcode 1143??).pdf [775.0 KB]
1. ?????????(leetcode 70??).pdf [2.8 MB]
4. ????????????(leetcode 300??).pdf [736.2 KB]
? ? ???
1. ??????(????????????????????????????).pdf [2.9 MB]
2. ?????(??????????????).pdf [3.0 MB]
? ? ??????
gbm-Freidman-1999.pdf [567.9 KB]
GBDT.pdf [3.3 MB]
xgboost.pdf [4.2 MB]
BoostedTree.pdf [1.4 MB]
xgboost paper.pdf [778.8 KB]
? ? 06??????
????.pdf [2.1 MB]
????????????????.pdf [451.6 KB]
??????AdaGrad??RMSProp??AdaDelta??Adam.pdf [747.6 KB]
?????????????????.pdf [1.3 MB]
? ? ?????????????
? ? ??????week1????????
? ? ???
iris_lr_demo.py [778.0 B]
LogisticRegression.py [3.0 KB]
LogisticRegression??.pdf [817.0 KB]
? ? ??????week1????????
? ? ???
04-Gini-Index.ipynb [17.1 KB]
01-What-is-Decision-Tree.ipynb [22.2 KB]
02-Entropy.ipynb [16.1 KB]
05-CART-and-Decision-Tree-Hyperparameters.ipynb [68.7 KB]
03-Entropy-Split-Simulation.ipynb [17.4 KB]
????????.pdf [423.1 KB]
? ? 03??????
? ? ????
????????????.pdf [374.6 KB]
logistics.py [915.0 B]
? ? hmm
? ? ??????
? ? data
199801???????.data [10.6 MB]
? ? model
hmm.model [301.2 KB]
hmm_segment.py [3.7 KB]
? ? ?????
? ? ????
??????.zip [112.2 KB]
? ? ?????????
code.zip [189.4 KB]
? ? SVM
? ? ????
03-SVM-Regressor.ipynb [3.3 KB]
01-SVM-in-scikit-learn.ipynb [70.0 KB]
02-RBF-Kernel-in-scikit-learn.ipynb [80.2 KB]
? ? ????
? ? ????
01-????????????????????????????.ipynb [226.8 KB]
1.png [25.1 KB]
02-????????????????????????.ipynb [66.6 KB]
04-Metropolis-Hastings???Beta????????.ipynb [26.7 KB]
03-????????????????.ipynb [5.5 KB]
? ? RNN??
RNN??.pdf [1.1 MB]
RNN.ipynb [27.3 KB]
? ? kmeans??
kmeans????.pdf [621.4 KB]
1.png [65.3 KB]
data.txt [610.0 B]
kmeans.ipynb [331.2 KB]
???????.png [493.5 KB]
???????.png [493.5 KB]
42.Week5?????????????????????????(leetcode1143??).mp4 [27.3 MB]
35.Week5????????????P4?????1.mp4 [20.6 MB]
45.Week5??????????????????????????????P2GRU??LSTM.mp4 [11.6 MB]
30.??????nlp?????????????????????baseline????.mp4 [108.2 MB]
22.Week3?????????????P4???????.mp4 [32.1 MB]
26.??????nlp???????????????????Baseline???.mp4 [70.2 MB]
06.Week1???????????????????P1??????.mp4 [20.3 MB]
10.Week2???????????????P3????SVM?????????????.mp4 [37.0 MB]
13.Week2???????????????P6smo??.mp4 [41.6 MB]
32.??????nlp????????????????????????????.mp4 [103.9 MB]
43.Week5?????????????????????????(leetcode300??).mp4 [24.1 MB]
30.Week4?????????????P4???????????.mp4 [24.6 MB]
11.Week2???????????????P4??????SVM.mp4 [24.5 MB]
49.Week6???????????????????????????P4????????????????.mp4 [11.7 MB]
33.??????nlp??????????????????????????????.mp4 [70.7 MB]
18.Week3??????????????????????K-means.mp4 [37.5 MB]
41.Week5?????????????leetcode416??01?????????.mp4 [36.4 MB]
34.Week5????????????P3??????????.mp4 [6.5 MB]
20.Week3?????????????P2???????????????.mp4 [51.6 MB]
47.Week6???????????????????????????P2???????????.mp4 [26.2 MB]
23.Week4????????????????????P1hmm????????????????.mp4 [27.1 MB]
04.Week1????????????????????????????????P3????????.mp4 [21.3 MB]
40.Week5?????????????01????????.mp4 [47.1 MB]
17.Week2????????????????????????PCA??LDA.mp4 [42.0 MB]
19.Week3?????????????P1????????.mp4 [59.3 MB]
27.Week4?????????????P1DFS??BFS.mp4 [34.9 MB]
12.Week2???????????????P5?????.mp4 [23.6 MB]
54.Week6??xgboost??????????????????P6???????.mp4 [11.1 MB]
31.??????nlp????????????????????baseline???????.mp4 [47.2 MB]
44.Week5??????????????????????????????P1RNN.mp4 [22.5 MB]
23.??????nlp??????????????????NLP???????????????-???????????.mp4 [33.7 MB]
29.??????nlp??????????????????????word2vec???.mp4 [73.1 MB]
15.Week2?????????????P2????????.mp4 [45.3 MB]
16.Week2?????????????P3?????.mp4 [21.9 MB]
09.Week2???????????????P2svm?????????.mp4 [16.9 MB]
07.Week1???????????????????P2??????.mp4 [24.1 MB]
48.Week6???????????????????????????P3??????????.mp4 [37.5 MB]
24.Week4????????????????????P2HMM??????????????.mp4 [39.9 MB]
14.Week2?????????????P1KMP??.mp4 [56.4 MB]
53.Week6??xgboost??????????????????P5?????????.mp4 [20.0 MB]
46.Week6???????????????????????????P1????????.mp4 [25.7 MB]
39.Week5??????????????????????(leetcode70??).mp4 [18.3 MB]
28.??????nlp???????????????tensorflow2.0????.mp4 [71.6 MB]
21.Week3?????????????P3????????????????.mp4 [22.2 MB]
29.Week4?????????????P3??????????.mp4 [25.9 MB]
26.Week4????????????????????P4crf???????.mp4 [31.3 MB]
27.??????nlp????????????????????????????????.mp4 [77.6 MB]
31.Week4?????????????P4????????????????????.mp4 [35.9 MB]
08.Week2???????????????P1????????????.mp4 [7.4 MB]
25.??????nlp????????????????????????????.mp4 [78.2 MB]
24.??????nlp??????????????????NLP???????????????-???????????????.mp4 [38.8 MB]
37.Week5???????????????????(????????????????????????????).mp4 [38.5 MB]
33.Week5????????????P2????.mp4 [14.1 MB]
32.Week5????????????P1????????????.mp4 [9.2 MB]
25.Week4????????????????????P3crf?????????????.mp4 [24.8 MB]
50.Week6??xgboost??????????????????P1xgboost??????????.mp4 [20.5 MB]
38.Week5??????????????????(??????????????).mp4 [66.3 MB]
36.Week5????????????P5?????2.mp4 [57.3 MB]
05.Week1????????????????????????????????P4????.mp4 [27.7 MB]
03.Week1????????????????????????????????P2??????.mp4 [27.0 MB]
01.????.mp4 [10.6 MB]
51.Week6??xgboost??????????????????P2????.mp4 [26.8 MB]
52.Week6??xgboost??????????????????P3????????????.mp4 [33.8 MB]
02.Week1????????????????????????????????P1????????.mp4 [29.7 MB]
28.Week4?????????????P2???????.mp4 [33.0 MB]??????
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