Purely out of curiosity, I’m recently reading the deep learning book (Goodfellow, Bengio, & Courville, 2016). I noticed that Chapter 2 Linear Algebra is a very quick and effective summary of linear algebra.

Although the concept of bias-variance trade-off is often discussed in machine learning textbooks, e.g., Bishop (2006), Hastie, Tibshirani, and Friedman (2009), James et al. (2013), I also find it important in almost any occasions in which we need to fit a statistical model on a data set with a limited number of observations.

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