This textbook is geared toward beginning graduate students from a variety of disciplines whose primary focus is not necessarily mathematics for its own sake. Instead, A Probability Path is designed for those requiring a deep understanding of advanced probability for their research in statistics, applied probability, biology, operations research, mathematical finance, and engineering.
As far as math textbooks go, this one is pretty strong in the level of detail of the proofs (less handwaving than readers of Rudin will be used to). It even has a sense of humor at times! My main criticism is the insufficient examples given for some of the trickier measure theoretic concepts that can be difficult to intuit. For instance there isn't a single example of finding a conditional expectation with respect to a random variable, in the cases where the undergrad method of using the conditional density isn't going to cut it.
Concept: graduate level probability for people who don't want or need to know measure theory. Geared particularly toward fields that can use martingale theory. I don't know if it succeeds on that score, you're never going to get your true finance meathead to understand conditional expectation (I have tried), but as a very concise and kind of informal presentation of the basics it's quite nice. Billingsley for people who can't be bothered. Kind of an unbalanced presentation with some serious editorial issues (a lot of errata and some misorganization). Lots of great exercises.