Best Genetic Algorithms
Since different candidates have different time constraints, EPI includes a study guide with several scenarios, ranging from weekend Hackathon to semester long preparation with a recommended a subset of problems for each scenario. All problems are classified in terms of their difficulty level and include many variants to help you apply what you have learned more widely. It emphasizes problems that stem from real-world applications. and can be coded up in a reasonable time, and is a wonderful complement to. a traditional computer science algorithms and data structures course. ".
Reviews
Find Best Price at Amazon"Better than most books of the same variant I've read and it is in Python."
"I have nothing but good things to say about the book, and can confidently say that no other product that offers as much depth as EoPI does. For example, if a problem has multiple solutions, the authors will walk you through each one and guide you towards the optimal solution. In addition to being a goldmine of commonly-asked problems, the book also offers many original problems that you wouldn't be able to find anywhere else; it is by far the most comprehensive practice resource out there."
"However, the physical quality of the book being delivered is horrible for a book lover like me. I ordered this book (brand new version ) from MT Rainier Store as a Christmas present for my brother on 21 Dec 2017 and it arrived on 26 Dec 2017. Although it may seems like very small details but for a book lover and as a Christmas present , the physical quality of the book really upset me."
"It covers bitwise operations and data structures, showing how to implement them from scratch and common interview problems. 3. A lengthy section called "Honors Class" with reach problems that exceed the difficulty in most tech interviews but are nonetheless fascinating to solve and build up confidence."
"After my last job I came to the conclusion that certain jobs will forever be out of my reach unless I will learn the fundamentals and the skills required to pass whiteboard interviews. I had to research and deepen my understanding (highly recommend the mycodeschool youtube channel). Because of the methodology of teaching through problems, it's extremely dense. I think python is the ideal language for interviews, because it's very concise and elegant and saves time writing the trivial stuff."
"Great book!"
2 Probably Approximately Correct: Natures Algorithms for Learning and Prospering in a Complex World
In Probably Approximately Correct , computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own. Offering a powerful and elegant model that encompasses life's complexity, Probably Approximately Correct has profound implications for how we think about behavior, cognition, biological evolution, and the possibilities and limits of human and machine intelligence. Because, Valiant dares to say, Darwin's theory is radically incomplete, and until it is equipped to make quantitative, verifiable predictions, evolution by natural selection cannot account for the complexity of living things and is not more than a metaphor.'. It's funny how your perception of even mundane tasks can change after reading ityou start thinking algorithmically, confirming Dr. Valiant's maxim that computer science is more about humans than about computers. This is a book that should be on every computer scientist's shelf so that when someone asks, Why is computer science theory important?'. A scholar at the intersection of computing and evolutionary neuroscience, Valiant explores ecorithms': algorithms that learn by interacting with their environment, not from their designerand so are fundamental to the process of evolution. This remarkable book is carefully constructed to give the lay person a sense of subtle problems in mathematics and artificial intelligence, and offers a framework for biologists and computer scientists to use in jointly investigating the most fascinating and enigmatic biological questions.” Marc Kirschner, Chair, Department of Systems Biology, Harvard Medical School, and coauthor of The Plausibility of Life: Resolving Darwin's Dilemma. Anyone interested in computation, learning, evolution, or human nature should find these pages extraordinarily stimulating and informative.” Stephen M. Kosslyn, Founding Dean, Minerva University, and former director, Center for Advanced Study in the Behavioral Sciences, Stanford University. It takes on the task of creating a quantitative, mathematical theory to explain all essential mechanisms governing the behavior of all living organisms: survival, learning, adaptation, evolution, cognition and intelligence.
Reviews
Find Best Price at Amazon"This idea was later generalised by Waddington - who proposed that genes could take over the trait completely - via a process known as "genetic assimilation". We see this effect in modern times, with learned milk drinking preceding genetically encoded lactose tolerance. Leslie says that "The idea that evolution is a form of learning sounds implausible to many people when they first hear it." Leslie asserts that, in Darwinian evolution, genetic variations are generated independently of current experiences - a constraint that does not apply to learning systems. However, Darwin was, in fact, a pioneer in the discovery of cultural evolution, writing about how words and languages were subject to natural selection. He minimizes the significance of cultural inheritance in other animals and the influence of individual learning on DNA evolution via the Baldwin effect and genetic assimilation. He says that before human culture: "the learning and reasoning carried out by an organism during its life had limited impact that outlived the individual". Also, we know that the idea that genetic variations are generated independently of current experiences is wrong - not least because of the role of stress in stimulating the production of mutations. Instead, Leslie sees Darwinian evolution as a primitive ladder that led to modern learning systems. He doesn't deal with the more powerful, generalized versions of evolutionary theory that also cover organisms that learn or make use of cultural transmission."
"The point to be made here is that if one is to view the brain as a computational entity that deploys various algorithms to deal with situations like this and survival in general one must come to grips with the computational complexity of these algorithms. The author of this book is well aware of the issues with computational complexity and via the idea (which he invented) of ‘probably approximately correct’ or PAC learning for short, has given the evolutionary biologists an interesting and provocative view of evolutionary processes that addresses some of the gaps in the Darwinian paradigm."
"PAC learning is an interesting paradigm but the writer obscures his argument for it as a path to describing evolution mathematically by spending so much time repeating his view that evolution lacks explanatory/predictive value."
"The book has some excellent ideas, but none of them are expanded enough."
3 Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World
In Probably Approximately Correct , computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own. Offering a powerful and elegant model that encompasses life's complexity, Probably Approximately Correct has profound implications for how we think about behavior, cognition, biological evolution, and the possibilities and limits of human and machine intelligence. Because, Valiant dares to say, Darwin's theory is radically incomplete, and until it is equipped to make quantitative, verifiable predictions, evolution by natural selection cannot account for the complexity of living things and is not more than a metaphor.'. It's funny how your perception of even mundane tasks can change after reading ityou start thinking algorithmically, confirming Dr. Valiant's maxim that computer science is more about humans than about computers. This is a book that should be on every computer scientist's shelf so that when someone asks, Why is computer science theory important?'. A scholar at the intersection of computing and evolutionary neuroscience, Valiant explores ecorithms': algorithms that learn by interacting with their environment, not from their designerand so are fundamental to the process of evolution. This remarkable book is carefully constructed to give the lay person a sense of subtle problems in mathematics and artificial intelligence, and offers a framework for biologists and computer scientists to use in jointly investigating the most fascinating and enigmatic biological questions.” Marc Kirschner, Chair, Department of Systems Biology, Harvard Medical School, and coauthor of The Plausibility of Life: Resolving Darwin's Dilemma. Anyone interested in computation, learning, evolution, or human nature should find these pages extraordinarily stimulating and informative.” Stephen M. Kosslyn, Founding Dean, Minerva University, and former director, Center for Advanced Study in the Behavioral Sciences, Stanford University. It takes on the task of creating a quantitative, mathematical theory to explain all essential mechanisms governing the behavior of all living organisms: survival, learning, adaptation, evolution, cognition and intelligence.
Reviews
Find Best Price at Amazon"This idea was later generalised by Waddington - who proposed that genes could take over the trait completely - via a process known as "genetic assimilation". We see this effect in modern times, with learned milk drinking preceding genetically encoded lactose tolerance. Leslie says that "The idea that evolution is a form of learning sounds implausible to many people when they first hear it." Leslie asserts that, in Darwinian evolution, genetic variations are generated independently of current experiences - a constraint that does not apply to learning systems. However, Darwin was, in fact, a pioneer in the discovery of cultural evolution, writing about how words and languages were subject to natural selection. He minimizes the significance of cultural inheritance in other animals and the influence of individual learning on DNA evolution via the Baldwin effect and genetic assimilation. He says that before human culture: "the learning and reasoning carried out by an organism during its life had limited impact that outlived the individual". Also, we know that the idea that genetic variations are generated independently of current experiences is wrong - not least because of the role of stress in stimulating the production of mutations. Instead, Leslie sees Darwinian evolution as a primitive ladder that led to modern learning systems. He doesn't deal with the more powerful, generalized versions of evolutionary theory that also cover organisms that learn or make use of cultural transmission."
"The point to be made here is that if one is to view the brain as a computational entity that deploys various algorithms to deal with situations like this and survival in general one must come to grips with the computational complexity of these algorithms. The author of this book is well aware of the issues with computational complexity and via the idea (which he invented) of ‘probably approximately correct’ or PAC learning for short, has given the evolutionary biologists an interesting and provocative view of evolutionary processes that addresses some of the gaps in the Darwinian paradigm."
"PAC learning is an interesting paradigm but the writer obscures his argument for it as a path to describing evolution mathematically by spending so much time repeating his view that evolution lacks explanatory/predictive value."
"The book has some excellent ideas, but none of them are expanded enough."
Best Memory Management Algorithms
Since different candidates have different time constraints, EPI includes a study guide with several scenarios, ranging from weekend Hackathon to semester long preparation with a recommended a subset of problems for each scenario. All problems are classified in terms of their difficulty level and include many variants to help you apply what you have learned more widely. It emphasizes problems that stem from real-world applications and can be coded up in a reasonable time, and is a wonderful complement to a traditional computer science algorithms and data structures course."
Reviews
Find Best Price at Amazon"This book is not an "easy" book compared with the other popular interview preparing books. (Just like how you train yourself in Gym). The pearls in this book are how the ideas are being developed and how one coding problem will evolve in different scenarios."
"Great book, I own both editions (C++ and Java) and highly recommend it to everybody."
"This is a great book with good problems and detailed explanations."
"This book is for advanced programmers, includes advanced Java language concepts."
"I am having interviews and getting asked a lot of questions from this very book."
"It's pretty good except the dynamic programming chapter."
"A must-have book if you are preparing for technical interviews."
Best Data Structure and Algorithms
A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. (Gabriel Robins, Department of Computer Science, University of Virginia) Introduction to Algorithms , the 'bible' of the field, is a comprehensive textbook covering the full spectrum of modern algorithms: from the fastest algorithms and data structures to polynomial-time algorithms for seemingly intractable problems, from classical algorithms in graph theory to special algorithms for string matching, computational geometry, and number theory.
Reviews
Find Best Price at Amazon"I actually bought it so that I could follow the MIT Computer Science course on OCW (open course ware), and though some chapters are a bit intimidating, I have learn much more than I expected."
"It's an Indian reprint version."
"It arrived in 3 days!"
""The Bible of the Algorithms" simply all you need to know, with enough mathematical rigor."
"Excellent reference for students or professionals."
"Useful text with many pseudo codes to study."
"This is a very authoritative book for algorithms and is a must-have for anyone who wants to have a comprehensive reference."
"Just bought the Third edition Hardcover."