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A lot of the questions asked by the various interviewers dealt with Schulz's religious beliefs, given the fact that many of the Peanuts comics had a religious tone to them. I found some of Schulz's comments interesting, but I never cared that much for those particular Peanuts strips, so a significant portion of this book didn't hold much interest for me.
It was interesting to see how the interviews conducted by writers employed by comic book magazines seemed very critical of Schulz related to the commercialization of Peanuts (i.e. Ford Motor ads in the 1960's, MetLife, etc.) I think Schulz handled these queries very well and also shows how tough he could be when pressed.
I think if you've read Rheta Johnson's terrific biography of Schulz and seen thegreat documentary on A&E, you'll have the best background of Schulz. This book is best served as a "fill in the blanks" supplement to those media.
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Unlike many writers on the subject of bird dogs, Waterman avoids maudlin sentiment. A big relief, since we do not need guidance in how to love and mourn our dogs.
One of the must have books for your hunting library.
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I have found that the pictures in this version of 'Puss' appeal immensely to kindergartners through third graders. (Fourth and Fifth grade children also like it, but are often embarassed to say so in a classroom setting!). Children who often have a hard time sitting still for a story have sat transfixed as I read this book, holding the pictures in front of them all the time and giving them lots of opportunities to check out the wonderful use of light and color. The illustrator uses a lot of wonderful yellow that is very appealing to young children and seems to draw them into the book. I love reading this book out loud both to see children's reaction and also because I love the detail and color in the pictures.
Reading this book aloud has also sparked some beautiful art work from young children.
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Known in computer science circles as CLR (for the authors) or simply, "The White Book", Introduction to Algorithms by Cormen, Leiserson, and Rivest is the de-facto standard text for algorithms and data structures. It covers all the basic subjects (big-O notation, trees, graphs, etc...) as well as a few intermediate subjects (amortized analysis, matroids, etc...). Of course, this book is not the be-all and end-all of computer science nor does it pretend to be. It touches on NP-completeness only lightly and all but omits randomization; but if you wanted a text on NP-completeness, you would be reading Garey & Johnson and if you wanted randomization you'd go to Motwani & Raghavan. But if you need a reference on data structures and algorithms, this is the book for you.
Now, some have complained that while this book is an excellent reference that it is a poor text to learn from. I beg to differ. I concede that it is certainly more demanding than many other introductory texts, but this is a boon not a curse. By remaining true to computer science's mathematical heritage, Cormen et al. force the reader to become accustomed to rigourous, formal reasoning, something which is unfortunately absent in many computer science curricula. The authors present the concepts cleanly and clearly, without the distraction of any specific programming language/paradigm. Perhaps it is this removal from a familiar C/C++/Java/flavour-of-the-month/etc... milieu which makes some readers nervous. But it is precisely this separation which forces the reader up into the realm of abstraction where computer science truly resides.
After a comprehensive overview of the mathematical foundations, the authors treat sorting algorithms, with heapsort, quicksort, and order statistics treated in great detail. They give an asymptotic analysis of the algorithms, and give an introduction to randomized algorithms in the discussion of quicksort. I found the discussion on order statistics very helpful for studying data polling algorithms in networks.
The authors then discuss data structures and how they can be used to construct algorithms for different problems. Queues, stacks, linked lists, and trees are discussed in detail, and the authors give asymptotic analyses for hashing and searching algorithms. The very important area of dynamic programming is also discussed at length. From the standpoint of someone interested in network modeling, I found the discussion of Dijkstra's algorithm especially well written. Unfortunately, the authors do not discuss in detail the Ajtai-Komlos-Szemeredi sorting algorithm. The treatment of this algorithm in the original paper is difficult reading so a better presentation would have been nice here. Parallel algorithms are given a nice treatment. The Fast Fourier Transform is given an interesting application to O(n lgn) multiplication of polynomials.
For readers interested in cryptography, the authors discuss the algorithm for the RSA cryptosystem. Primality testing is also treated, with the Miller-Rabin probabilistic algorithm given a nice treatment. The Pollard rho method for integer factorization is also discussed.
I found the discussion of string matching also very useful from the standpoint of computational biology. The Rabin-Karp and Knuth-Morris-Pratt algorithms are both treated in great detail.
A short but good introduction to algorithms in computational geometry, such as the gift-wrapping algorithm in convex geometry, is given.
The authors thus cover a large amount of material here, and each chapter could itself be a 1000-page book. But their selection of algorithms in each of the areas covered serves well to introduce the reader to the more popular ones available. A large list of references is given for further reading on revisions and extensions to these algorithms.