+   [Machine Learning Mastery 机器学习入门教程](README.md)
+   [机器学习入门的四个步骤：初学者入门与实践的自上而下策略](4-steps-to-get-started-in-machine-learning.md)
+   [你应该培养的 5 个机器学习领域](5-machine-learning-areas-you-should-be-cultivating.md)
+   [一种选择机器学习算法的数据驱动方法](a-data-driven-approach-to-machine-learning.md)
+   [机器学习中的分析与数值解](analytical-vs-numerical-solutions-in-machine-learning.md)
+   [应用机器学习是一种精英政治](applied-machine-learning-is-a-meritocracy.md)
+   [机器学习的基本概念](basic-concepts-in-machine-learning.md)
+   [如何成为数据科学家](become-data-scientist.md)
+   [初学者如何在机器学习中弄错](beginners-get-it-wrong.md)
+   [机器学习的最佳编程语言](best-programming-language-for-machine-learning.md)
+   [构建机器学习组合](build-a-machine-learning-portfolio.md)
+   [机器学习中分类与回归的区别](classification-versus-regression-in-machine-learning.md)
+   [评估自己作为数据科学家并利用结果建立惊人的数据科学团队](data-science-skills-simple-method-can-use-evaluate-use-results-build-amazing-data-science-teams.md)
+   [探索 Kaggle 大师的方法论和心态：对 Diogo Ferreira 的采访](discover-the-methodology-and-mindset-of-a-kaggle-master-an-interview-with-diogo-ferreira.md)
+   [扩展机器学习工具并展示掌握](extend-machine-learning-tools.md)
+   [通过寻找地标开始机器学习](find-machine-learning-landmarks.md)
+   [温和地介绍预测建模](gentle-introduction-to-predictive-modeling.md)
+   [通过提供结果在机器学习中获得梦想的工作](get-dream-job-machine-learning-delivering-results.md)
+   [如何开始机器学习：自学蓝图](get-started-machine-learning.md)
+   [开始并在机器学习方面取得进展](get-started-make-progress-machine-learning.md)
+   [应用机器学习的 Hello World](hello-world-of-applied-machine-learning.md)
+   [初学者如何使用小型项目开始机器学习并在 Kaggle 上进行竞争](how-a-beginner-used-small-projects-to-get-started-in-machine-learning-and-compete-on-kaggle.md)
+   [我如何开始机器学习？ （简短版）](how-do-i-get-started-in-machine-learning.md)
+   [我是如何开始机器学习的](how-i-got-started-in-machine-learning.md)
+   [如何在机器学习中取得更好的成绩](how-to-get-better-at-machine-learning.md)
+   [如何从在银行工作到担任 Target 的高级数据科学家](how-to-go-from-working-in-a-bank-to-hired-as-senior-data-scientist-at-target.md)
+   [如何学习任何机器学习工具](how-to-learn-any-machine-learning-tool.md)
+   [使用小型目标项目深入了解机器学习工具](investigate-machine-learning-tools.md)
+   [获得付费申请机器学习](ladder-approach-to-becoming-a-machine-learning-consultant.md)
+   [映射机器学习工具的景观](list-machine-learning-tools.md)
+   [机器学习开发环境](machine-learning-development-environment.md)
+   [机器学习金钱](machine-learning-for-money.md)
+   [程序员的机器学习](machine-learning-for-programmers.md)
+   [机器学习很有意思](machine-learning-is-fascinating.md)
+   [机器学习是 Kaggle 比赛](machine-learning-is-kaggle-competitions.md)
+   [机器学习现在很受欢迎](machine-learning-is-popular.md)
+   [机器学习掌握方法](machine-learning-mastery-method.md)
+   [机器学习很重要](machine-learning-matters.md)
+   [机器学习 Q＆amp; A：概念漂移，更好的结果和学习更快](machine-learning-qa-concept-drift-better-results-and-learning-faster.md)
+   [缺乏自学机器学习的路线图](machine-learning-roadmap-your-self-study-guide-to-machine-learning.md)
+   [机器学习很重要](machine-learning-that-matters.md)
+   [快速了解任何机器学习工具（即使您是初学者）](machine-learning-tool-templates.md)
+   [机器学习工具](machine-learning-tools.md)
+   [找到你的机器学习部落](machine-learning-tribe.md)
+   [机器学习在一年](machine-learning-year.md)
+   [通过竞争一致的大师 Kaggle](master-kaggle-by-competing-consistently.md)
+   [5 程序员在机器学习中开始犯错误](mistakes-programmers-make-when-starting-in-machine-learning.md)
+   [哲学毕业生到机器学习从业者（Brian Thomas 采访）](philosophy-graduate-to-machine-learning-practitioner.md)
+   [机器学习入门的实用建议](practical-advice-for-getting-started-in-machine-learning.md)
+   [实用机器学习问题](practical-machine-learning-problems.md)
+   [使用来自 UCI 机器学习库的数据集练习机器学习](practice-machine-learning-with-small-in-memory-datasets-from-the-uci-machine-learning-repository.md)
+   [使用秘籍的任何机器学习工具快速启动](proceduralize-machine-learning-tools.md)
+   [程序员可以进入机器学习](programmers-can-get-into-machine-learning.md)
+   [程序员应该进入机器学习](programmers-should-get-into-machine-learning.md)
+   [项目焦点：Shashank Singh 的人脸识别](project-spotlight-face-recognition-with-shashank-singh.md)
+   [项目焦点：使用 Mahout 和 Konstantin Slisenko 进行堆栈交换群集](project-spotlight-stack-exchange-clustering-using-mahout-with-konstantin-slisenko.md)
+   [机器学习自学指南](self-study-guide-to-machine-learning.md)
+   [4 个自学机器学习项目](self-study-machine-learning-projects.md)
+   [ÁlvaroLemos 如何在数据科学团队中获得机器学习实习](student-got-machine-learning-internship-job-data-science-team.md)
+   [如何思考机器学习](think-machine-learning.md)
+   [现实世界机器学习问题之旅](tour-of-real-world-machine-learning-problems.md)
+   [有关机器学习的有用知识](useful-things-to-know-about-machine-learning.md)
+   [如果我没有学位怎么办？](what-if-i-dont-have-a-degree.md)
+   [如果我不是一个优秀的程序员怎么办？](what-if-im-not-a-good-programmer.md)
+   [如果我不擅长数学怎么办？](what-if-im-not-good-at-mathematics.md)
+   [为什么机器学习算法会处理以前从未见过的数据？](what-is-generalization-in-machine-learning.md)
+   [是什么阻碍了你的机器学习目标？](what-is-holding-you-back-from-your-machine-learning-goals.md)
+   [什么是机器学习？](what-is-machine-learning.md)
+   [机器学习适合哪里？](where-does-machine-learning-fit-in.md)
+   [为什么要进入机器学习？](why-get-into-machine-learning.md)
+   [研究对您来说很重要的机器学习问题](work-on-machine-learning-problems-that-matter-to-you.md)
+   [你这样做是错的。为什么机器学习不必如此困难](youre-wrong-machine-learning-not-hard.md)