# Tag Info

Accepted

### What is an intuitive explanation for how PCA turns from a geometric problem (with distances) to a linear algebra problem (with eigenvectors)?

Problem statement The geometric problem that PCA is trying to optimize is clear to me: PCA tries to find the first principal component by minimizing the reconstruction (projection) error, which ...
• 105k
Accepted

### Why is XOR not linearly separable?

Draw a picture. The question asks you to show it is not possible to find a half-plane and its complement that separate the blue points where XOR is zero from the red points where XOR is one (in the ...
• 326k
Accepted

• 326k
Accepted

### Should I gloss over the linear algebra chapter in the book "Deep Learning" by Ian Goodfellow?

This is a question that often pops up when reading mathematical literature. The initial chapters, of this book or any other math book, lay out tools that you will be using in later chapters, so ...
• 125k

### What is the intuition behind SVD?

Take an hour of your day and watch this lecture. This guy is super straight-forward; It's important not to skip any of it because it all comes together in the end. Even if it might seem a little slow ...
• 131

### Multivariate normal posterior

With the distributions on our random vectors: $\mathbf x_i | \mathbf \mu \sim N(\mu , \mathbf \Sigma)$ $\mathbf \mu \sim N(\mathbf \mu_0, \mathbf \Sigma_0)$ By Bayes's rule the posterior ...
• 4,236

### Why are symmetric positive definite (SPD) matrices so important?

You'll find some intuition in the many elementary ways of showing the eigenvalues of a real symmetric matrix are all real: https://mathoverflow.net/questions/118626/real-symmetric-matrix-has-real-...
• 14k
### What is the problem with $p > n$?
This is a very good question. When the number of candidate predictors $p$ is more than the effective sample size $n$, and one does not place any restrictions on the regression coefficients (e.g., one ...