Feature Engineering for Machine Learning
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2019-01-10
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Feature Engineering for Machine Learning （196个子文件） 
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index.html 3KB pack-45dc0c185c799da626067564d23f0a292fb7e7c4.idx 17KB index 17KB
5-6.jpg 276KB 5-9.jpg 163KB 5-2.jpg 141KB 5-1.jpg 133KB 5-7.jpg 130KB cover.jpg 67KB 5-3.jpg 12KB 5-5.jpg 11KB 5-4.jpg 8KB process_tex.js 1KB master 198B master 41B 2.简单数字的奇特技巧.md 47KB 8.自动化特征提取器：图像特征提取和深度学习.md 31KB 6.降维：用_PCA_压缩数据集.md 30KB 3.文本数据.md 30KB 5.类别特征.md 29KB 4.特征缩放的效果：从词袋到_TF-IDF.md 27KB 7.非线性特征提取和模型堆叠.md 21KB 附录.线性模型和线性代数基础.md 19KB 1.引言.md 10KB README.md 3KB SUMMARY.md 865B .nojekyll 0B pack-45dc0c185c799da626067564d23f0a292fb7e7c4.pack 14.85MB packed-refs 107B
Feature Engineering for Machine Learning_Principles and Techniques for Data Scientists(2018.03).A4.pdf 7.2MB pic 1B
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