I know it is expensive and massive but I really think every developer should have a copy of CLRS. It is well organized, well written, and extremely thorough. In fact I was just paging through it today to review a few graph algorithms.
I second Big O notation and this whole idea. I didn't do an entire computer science degree, but I did some, and these concepts are what have stuck with me as considerations that come up a lot.
Time to write my Big O practical applications essay. Still need to fully understand it though. I read a great book about CS concepts written by someone who didn't have a CS degree. Not an ad but a good book.
Big O notation, an understanding of what algorithms are "expensive," and an understanding of what happens with "expensive" algorithms at large scales.
For some reason at my CS degree we hardly touched on Big O. Does anyone have some great resources for gaining a better understanding?
I know it is expensive and massive but I really think every developer should have a copy of CLRS. It is well organized, well written, and extremely thorough. In fact I was just paging through it today to review a few graph algorithms.
I second Big O notation and this whole idea. I didn't do an entire computer science degree, but I did some, and these concepts are what have stuck with me as considerations that come up a lot.
Time to write my Big O practical applications essay. Still need to fully understand it though. I read a great book about CS concepts written by someone who didn't have a CS degree. Not an ad but a good book.
bigmachine.io/products/the-imposte...
Ah, someone beat me to it I see :)
I couldn't agree more about this recommendation.