For #3, I was basically looking for some feedback on this text. It was recommended in the best textbooks on every subject thread, but I’ve heard mixed reviews about it. The top rated review on amazon claims
Students will need a very strong mathematical background and a strong arm to even think about picking up this book because the it is heavy (both physically and metaphorically). Mastery of discrete math is a must, graph theory, programming, and, combinatorics will also help.
and another review by a Comp Sci professor calls it “Magisterial, and Impenetrable”.
These are not things you see written about something like Sedgewick’s book. Interestingly enough, the reviews on this one all similarly praise Sedgewick’s book over Cormen.
So I guess my question was “Is Cormen et al. actually a good introductory text on algorithms for someone who has not taken an algorithms course before?”
The answer is “probably not”. Cormen is too comprehensive and dry for self-study; it’s best used as the textbook to back an algorithms course or as a reference to consult later on.
A very good book is Skiena, The Algorithm Design Manual. I usually recommend it to people who want to brush up on their algorithms before programming interviews, but I think it’s accessible enough to a novice as well. Its strengths are an intelligent selection of topics and an emphasis on teaching how to select an algorithm in a real-life situation.
How much of a mathematician are you? I would recommend Cormen et al on its own only to people with a strong mathematical background and plenty of talent. I like the idea of Cormen et al + Skiena together (and I’m pretty sure I said so in that thread) but don’t have actual evidence on how well that works in practice.
Ah, sorry, I was referring to your question about Jaynes (that question was meant to be numbered with a 4). What are you looking to get out of an introductory probability textbook?
Thanks, that’s really helpful.
For #3, I was basically looking for some feedback on this text. It was recommended in the best textbooks on every subject thread, but I’ve heard mixed reviews about it. The top rated review on amazon claims
and another review by a Comp Sci professor calls it “Magisterial, and Impenetrable”.
These are not things you see written about something like Sedgewick’s book. Interestingly enough, the reviews on this one all similarly praise Sedgewick’s book over Cormen.
So I guess my question was “Is Cormen et al. actually a good introductory text on algorithms for someone who has not taken an algorithms course before?”
The answer is “probably not”. Cormen is too comprehensive and dry for self-study; it’s best used as the textbook to back an algorithms course or as a reference to consult later on.
A very good book is Skiena, The Algorithm Design Manual. I usually recommend it to people who want to brush up on their algorithms before programming interviews, but I think it’s accessible enough to a novice as well. Its strengths are an intelligent selection of topics and an emphasis on teaching how to select an algorithm in a real-life situation.
How much of a mathematician are you? I would recommend Cormen et al on its own only to people with a strong mathematical background and plenty of talent. I like the idea of Cormen et al + Skiena together (and I’m pretty sure I said so in that thread) but don’t have actual evidence on how well that works in practice.
Ah, sorry, I was referring to your question about Jaynes (that question was meant to be numbered with a 4). What are you looking to get out of an introductory probability textbook?