教学参考用书1.《
机器学习实战》
-[美]Peter Harrington 著
-人民邮电出版社
2.《统计学习方法》
李航著，清华大学出版社
3.《金融
数据挖掘与分析》
郑志明等著，机械工业出版社
4.《Scikit-Learn与TensorFlow机器学习实用指南》
Aurélien等著，东南大学出版社
5.《数据挖掘 概念与技术》
Jiawei Han等著，机械工业出版社
在线资料：网页版教材：
http://ml.apachecn.org/mlia/
教材数据集（公众号中有按授课安排梳理的数据集）：
https://www.manning.com/books/machine-learning-in-action Scikit-learn中文手册：
http://sklearn.apachecn.org/cn/0.19.0/
Python 3在线教程：
http://www.runoob.com/python3/python3-tutorial.html吴恩达（Andrew Ng）
深度学习项目：
https://www.deeplearning.ai/
本课程所用Python基础知识与《量化投资分析》课程相当，第2章会对重要知识点进行简单回顾，请同学们适当复习相关内容。
+data 8.0 MB
|+CH03 1.5 MB
| |+EX01 61.3 KB
| |+EX02 723.0 KB
| |+EX03 2.1 KB
| |+EX04 62.9 KB
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|+CH04 219.0 KB
| |+EX01 5.5 KB
| |+EX02 193.0 KB
| |+EX03 3.8 KB
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| |+EX06 8.3 KB
|+CH05 189.0 KB
| |+EX01 1.6 KB
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| |+EX03 186.0 KB
|+CH06 5.2 MB
|+EXAM 897.0 KB
| 2 apriori.zip 897.0 KB
+pic 171.0 KB
| 3-1 Logit的故事.html 171.0 KB
+考试 46.7 MB
| 附件一：scikit-learn-docs.pdf 46.3 MB
| 仙林-金融数据挖掘.pdf 355.0 KB
+课件 30.2 MB
| 第1章 绪论.pdf 2.8 MB
| 第2章 语言.pdf 1.0 MB
| 第3章 分类.pdf 10.9 MB
| 第4章 预测.pdf 7.2 MB
| 第5章 聚类.pdf 4.7 MB
| 第6章 降维.pdf 3.6 MB
+原始数据集 38.8 MB
|+Ch02 737.0 KB
| |+EXTRAS 5.2 KB
| | digits.zip 723.0 KB
| | kNN.py 4.2 KB
| | kNN.pyc 4.4 KB
| | README.txt 240 Byte
| | testSet.txt 0 Byte
|+Ch03 15.7 KB
| | classifierStorage.txt 101 Byte
| | lenses.txt 795 Byte
| | treePlotter.py 3.8 KB
| | treePlotter.pyc 3.3 KB
| | trees.py 4.1 KB
| | trees.pyc 3.6 KB
|+Ch04 44.4 KB
| |+email 13.9 KB
| |+EXTRAS 1.9 KB
| | bayes.py 7.1 KB
| | bayes.pyc 6.8 KB
| | email.zip 14.8 KB
|+Ch05 79.2 KB
| |+EXTRAS 5.7 KB
| | horseColicTest.txt 3.7 KB
| | horseColicTraining.txt 59.2 KB
| | logRegres.py 4.0 KB
| | logRegres.pyc 4.4 KB
| | testSet.txt 2.1 KB
|+Ch06 155.0 KB
| |+EXTRAS 4.5 KB
| | digits.zip 127.0 KB
| | svmMLiA.py 15.9 KB
| | testSet.txt 2.2 KB
| | testSetRBF.txt 2.9 KB
| | testSetRBF2.txt 2.9 KB
|+Ch07 87.3 KB
| |+EXTRAS 1.3 KB
| | adaboost.py 5.4 KB
| | adaboost.pyc 4.6 KB
| | horseColicTest2.txt 13.3 KB
| | horseColicTraining2.txt 59.3 KB
| | old_adaboost.py 3.4 KB
|+Ch08 662.0 KB
| |+setHtml 436.0 KB
| | abalone.txt 193.0 KB
| | ex0.txt 5.5 KB
| | ex1.txt 5.5 KB
| | Old_regression.py 7.4 KB
| | regression.py 8.3 KB
| | regression.pyc 6.8 KB
|+Ch09 48.7 KB
| | bikeSpeedVsIq_test.txt 4.1 KB
| | bikeSpeedVsIq_train.txt 4.1 KB
| | ex0.txt 5.5 KB
| | ex00.txt 3.8 KB
| | ex2.txt 4.0 KB
| | ex2test.txt 4.0 KB
| | exp.txt 3.9 KB
| | exp2.txt 3.7 KB
| | expTest.txt 3.9 KB
| | regTrees.py 5.6 KB
| | sine.txt 3.8 KB
| | treeExplore.py 2.3 KB
|+Ch10 471.0 KB
| | kMeans.py 6.3 KB
| | kMeans.pyc 6.2 KB
| | places.txt 4.6 KB
| | Portland.png 448.0 KB
| | portlandClubs.txt 3.0 KB
| | testSet.txt 1.6 KB
| | testSet2.txt 1.2 KB
|+Ch11 748.0 KB
| | apriori.py 5.8 KB
| | apriori.pyc 5.1 KB
| | bills20DataSet.txt 38.0 KB
| | lawAssnRules.txt 134.0 KB
| | meaning20.txt 1.8 KB
| | mushroom.dat 557.0 KB
| | recent100bills.txt 5.5 KB
| | recent20bills.txt 1.0 KB
|+Ch12 30.5 MB
| | fpGrowth.py 6.5 KB
| | kosarak.dat 30.5 MB
|+Ch13 5.2 MB
| |+extras 3.7 KB
| | iris.data.txt 4.4 KB
| | pca.py 1.3 KB
| | pca.pyc 1.5 KB
| | secom.data 5.1 MB
| | testSet.txt 19.0 KB
| | testSet3.txt 21.6 KB
|+Ch14 9.4 KB
| | 0_5.txt 1.1 KB
| | svdRec.py 3.9 KB
| | svdRec.pyc 4.5 KB
|+Ch15 99.0 KB
| | err.txt 2.7 KB
| | inputFile.txt 900 Byte
| | junk.txt 61 Byte
| | kickStart.txt 1.1 KB
| | mrMean.py 1.3 KB
| | mrMeanMapper.py 658 Byte
| | mrMeanReducer.py 819 Byte
| | mrSVM.py 3.4 KB
| | mrSVMkickStart.py 255 Byte
| | myfile.txt 6.0 KB
| | myout.txt 6.0 KB
| | pegasos.py 2.4 KB
| | proximalSVM.py 1.7 KB
| | py27dbg.py 585 Byte
| | svmDat2.txt 15.5 KB
| | svmDat26 15.5 KB
| | svmDat27 15.5 KB
| | svmData.txt 15.5 KB
| | testSet.txt 4.4 KB
| | testSet200.txt 4.4 KB
| | wc.py 781 Byte
| README.rst 653 Byte
data.zip 3.6 MB
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