Many good resources have already been named, so I won't repeat them here.
As for how do you know what algorithm to use when?
You need to have a big enough tool box, which you will obtain by sitting down and slogging through a long list of basic (and them more esoteric) data structures and algorithms. You should try to get all the basics, but really only need a sample from the more specialized ones.
You need to understand what trade offs are available to you (time, code complexity, memory, single versus multiple passes, in-place versus copy, stable versus unstable sorts, etc. ad nauseum), and how the algorithms you study do on each of these. Again, this is just a case of much studying. Big-O is a place to start, but is not the end all and be all of this.
You need to get a feel for understanding what are the real limits you face when presented with a problem, and how to express these in terms of the algorithm trade offs mentioned above. This requires a degree of intuition, and is generally learned by practice over time.
It is worth implementing some things more then one way as you go along, to learn in your gut, what works and what doesn't.
It is worth reading code written by folks more experienced than yourself, to see how they think.
Good luck.
