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The Algorithm Design Manual

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What I like about this book is that, it does not talk about what a particular algorithm does and how it is implemented, but more it takes you on a flight between two algorithms. The book builds a way of thinking towards solving algorithms problems, instead of just stating the algorithms and data structures in a mechanical way, but in many parts it is not very clear and you have to read a passage multiple times to understand what the author meant. In a mature ecosystem like Python, a lot of the time the right answer is just "pip install magiclib.

Addressing the main difficulties of solving problems, this book goes far beyond the design of algorithms. He is the author of four books, including "The Algorithm Design Manual" and "Calculated Bets: Computers, Gambling, and Mathematical Modeling to Win". Clear explainers are interspersed with practical war stories, where Skiena explains how he applied the technique just discussed to solve a previously intractable problem. In comparison to "Introduction to Algorithms" (the other algorithm book I had significant exposure to) this one is faster to read, easier to digest and more tailored towards applications.He is the author of six well-regarded books: The Algorithm Design Manual (2020), The Data Science Design Manual (2017), Who's Bigger (2013), Calculated Bets: Computers, Gambling, and Mathematical Modeling to Win (2001), Programming Challenges (with Miguel Revilla, 2003) and Computational Discrete Mathematics (with Sriram Pemmaraju, 2003). Every programmer should read this book, and anyone working in the field should keep it close to hand. A unique and illuminating feature of this book is an extensive collection of "war stories" describing the author's personal experiences with applying these algorithmic tools in various circumstances (quite fascinating, and some a bit darkly humorous). For someone who's never taken CS101, this book an eye-opener into the hows and whys of basic data structures like linked lists, trees, hash tables, and arrays, as well as sorting techniques and more advanced practices like dynamic programming.

The book spends a lot of time emphasizing the utility of graph algorithms and how to model various classes of problems with them, as well as lot of time on dynamic programming and backtracking/enumeration. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis.

over 30 hours of audio lectures on the design and analysis of algorithms are provided, all keyed to on-line lecture notes. If you were a professional programmer trying to earn a living, you would want to do even better: programme the computer to find the best way of finding a route (fastest, smallest, most accurate, suitable for wide loads, avoiding speed cameras . Megan Squire, Elon University, USA This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency.

I've found that a lot of computer programming is easy if you just know the name of thing you need to Google. One of Skiena's "war stories" tells of making a program run 30,000 times faster by using a better-designed algorithm.The Algorithm Design Manual by Steven Skiena is aimed at two groups of people: students and professionals. The 103 third parties who use cookies on this service do so for their purposes of displaying and measuring personalized ads, generating audience insights, and developing and improving products.

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