Mastering Machine Learning with scikit-learn - Second Edition

关于sklearn中一些主要模型的介绍，包括：脚本、模型背后简单的数学原理、案例，非常适合通过sklearn入门机器学习。章节包括：

从案例分类包括：
1. 自然语言处理
2. 图像处理
3. 商业数据分析

关于可视化虽然有提到，但是不是很多。

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
learning_text		learning_text
README.md		README.md
chapter_03_Feature_Extraction.ipynb		chapter_03_Feature_Extraction.ipynb
chapter_05_multiple_linear_regression.ipynb		chapter_05_multiple_linear_regression.ipynb
chapter_06_from_linearregression_to_logistic_regression.ipynb		chapter_06_from_linearregression_to_logistic_regression.ipynb
chapter_07_Naive_Bayes.ipynb		chapter_07_Naive_Bayes.ipynb
chapter_08_Nonlinear_Classification_and_Regression_with_Decision_Trees.ipynb		chapter_08_Nonlinear_Classification_and_Regression_with_Decision_Trees.ipynb
chapter_09_From_Decision_Trees_to_Random_Forests_and_Other_Ensemble_Methods.ipynb		chapter_09_From_Decision_Trees_to_Random_Forests_and_Other_Ensemble_Methods.ipynb
chapter_10_Perceptron.ipynb		chapter_10_Perceptron.ipynb
chapter_11_from_perceptron_to_support_vector_machine.ipynb		chapter_11_from_perceptron_to_support_vector_machine.ipynb
chapter_12_From_the_Perceptron_to_Aritificial_Neural_Networks.ipynb		chapter_12_From_the_Perceptron_to_Aritificial_Neural_Networks.ipynb
chapter_13_Kmeans.ipynb		chapter_13_Kmeans.ipynb
chapter_14_Dimensionality_Reduction_with_Principal_Component_Analysis.ipynb		chapter_14_Dimensionality_Reduction_with_Principal_Component_Analysis.ipynb

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