NG的手稿，并没有出全，当前只出到14章。我这里边学习边翻译记录之，加深学习印象。
更好阅读体验，移步gitbook：https://xiaqunfeng.gitbooks.io/machine-learning-yearning/content/
这本书的目的是教你如何做组织一个机器学习项目所需的大量的决定。 你将学习：
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如何建立你的开发和测试集
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基本错误分析
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如何使用偏差和方差来决定该做什么
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学习曲线
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将学习算法与人类水平的表现进行比较
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调试推理算法
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什么时候应该和不应该使用端到端的深度学习
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按部进行错误分析
Chapter 1、Why Machine Learning Strategy
Chapter 2、How to use this book to help your team
Chapter 3、Prerequisites and Notation
Chapter 4、Scale drives machine learning progress
Chapter 5、Your development and test sets
Chapter 6、Your dev and test sets should come from the same distribution
Chapter 7、How large do the dev/test sets need to be?
Chapter 8、Establish a single-number evaluation metric for your team to optimize
Chapter 9、Optimizingandsatisficingmetrics
Chapter 10、Having a dev set and metric speeds up iterations
Chapter 11、When to change dev/test sets and metrics
Chapter 12、Takeaways: Setting up development and test sets
Chapter 13、Error analysis: Look at dev set examples to evaluate ideas
Chapter 14、Evaluate multiple ideas in parallel during error analysis
...
当前更新了14章，下载链接如下：