The Mercedes Thompson series by Patricia Briggs. Main character is a coyote shapeshifter in a world with werewolves, vampires, fae, and they hint that there are worse things out there. I rather like them. They're fast paced, have solid character development, and have one of the more interesting main characters I've seen before.
Honor Harrington by David Weber. Wonderful, glorious Science Fiction. The numbers he gives are apparently not quite right at times, but on the whole, he does a pretty darn good job of things. There's nothing so glaringly wrong that I can't overlook it, and to be honest, the only people that really care are the fan-nazis who demand perfection. The books themselves have good plots and pacing, though in a few places the story slows a bit as he gets a bit more into the details needed to explain certain points. Sometimes that's okay, and sometimes it's not. Overall, highly recommended.
And of course, The Dresden Files are always on my reading list, though the next one is a little ways out still...
Edit: Algorithms in a Nutshell. I absolutely can't forget the wonderful little book I'm using right now. It isn't one you just read through (though I probably will one of these days), because it's a reference book. But what a reference book it is! It gives detailed implementations and descriptions of a number of different algorithms, as well as optimizations and performance evaluations.
It starts with classic sorting and searching, but quickly moves to other topics, such as graphs, computational geometry, and pathfinding. Their coverage of Best/Average/Worst case theory is a bit thin, but they even say on the back cover that it's just enough to allow you to understand and compare performance, which is fine with me. I honestly don't need yet another course in performance analysis, tyvm!
Overall, this book is an excellent reference, and even without having used it much, I already have gotten my money's worth. Any suggestions for other books like this?