# Comments to the Book on Probabilistic Machine Learning

## 6 thoughts on “Comments to the Book on Probabilistic Machine Learning”

1. Anonymous says:

Kind Regards, Elmar Rueckert

2. Anonymous says:

2.3 Logistic Regression

> where σ’ denotes the sigmoid function in Equation 2.4. Note that the
function φ(x) in Equation 2.2 may be in the simple lear* model the
identity function φ(x) = x.

simple linear* model

3. Anonymous says:

Missing blank space at the bottom of page 15: To better visualize the difference to ridge regression in Equation2.12 and ..

Remark 2.5.1 makes no sense to me in terms of content (Intuitively, such a model make sense as for noisy data that much and hence regularize more.).

In Remark 2.6.1 there is a dot instead of a comma in the last sentence.
Directly after the remark mu is described as parameter uncertainty, but as I understood the parameter uncertainty will be described by sigma.

4. Anonymous says:

Section 1.6 Beta Distribution:

The formula for the Beta Distribution is wrong. Either it should be Beta(x|a,b) := B(a,b)… (so no inverse on the B function) or B(a,b) = (g(a)g(b))/(g(a+b)) where g() is the gamma function.

5. Anonymous says:

1. The formula for Beta distribution is wrong. Should be either: Beta(x|a,b) = B(a,b) … (ie. without the inverse) or : B(a,b) = gamma(a)gamma(b)/gamma(a+b)

2. The equation 1.8 and 1.9 are wrong. It should be (1.8): mu_a|b = … and not mu_b|a = …
and for 1.9 it should be: Sigma_a|b = …… and not Sigma_b|a = …..

6. Anonymous says:

Failure in Appendix Least Squares page 41:
the last term must be: (y-wA) //not transposed.