Also Bishop is much harder to read, so for a first introduction I think that Mitchell is good. There are some chapters on theoretical learning that you can skip, but I do think that it is good for a first overview of the field.
This is the first time I hear about Marsland's book, so I can't comment on that.
One book that I would suggest to anyone is Introduction to Automata Theory, Languages, and Computation - HMU. It is very approachable and presents some very interesting topics (so you won't write a regex for matching HTML and will learn what P vs NP means). On a more practical side, I think that a must read for machine learning is Tom Mitchell - Machine Learning . Another book that from what I've heard is easier to digest is Data Mining: Practical Machine Learning Tools and Techniques.
Whatever you do, it doesn't matter. A boatload of companies have tried to fiercely combat piracy - not a single success. So why even bother and waste money in various methods, it only delays (in a matter of days ?) the crack.