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Best Computer Algorithms

Introduction to Algorithms, 3rd Edition (MIT Press)
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
"It is a very nice book, but sometimes you can find a simpler description/explanation of some algorithms."
"Now 8 years later, I bought the third edition to renew these knowledge."
"However, it's still an introduction to algorithms, although it's already hard for most of averaged students."
"I love this book."
"This textbook isn't just a textbook for an algorithms class."
"Gives complete and deep explanation on topics covered."
"This type of material is easier to read on a wide screen."
"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."
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Algorithms (4th Edition)
This fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms is the leading textbook on algorithms today and is widely used in colleges and universities worldwide. The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. Robert Sedgewick has been a Professor of Computer Science at Princeton University since 1985, where he was the founding Chairman of the Department of Computer Science.
Reviews
"I really enjoy reading this book."
"A very updated and well written book about algorithms and data structures."
"Excellent book for beginners and advance students of computer science."
"Excellent book on essential algorithms and data structures."
"It's a bit hard but example codes gives better understanding for the concepts."
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Introduction to Algorithms, Third Edition (International Edition)
"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
"It is a very nice book, but sometimes you can find a simpler description/explanation of some algorithms."
"Now 8 years later, I bought the third edition to renew these knowledge."
"However, it's still an introduction to algorithms, although it's already hard for most of averaged students."
"I love this book."
"This textbook isn't just a textbook for an algorithms class."
"Gives complete and deep explanation on topics covered."
"This type of material is easier to read on a wide screen."
"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."
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Best Programming Algorithms

Introduction to Algorithms, 3rd Edition (MIT Press)
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
"I have attended several major Southern California universities, all computer instructors bow to this text."
"If you don't understand any terms or even some of the math that is shown, the appendix and sections in the back will tell you everything you need to know."
"This is widely considered the one algorithms book that every computer science should read."
"Book."
"Very thorough and complete book, although a bit hard to read."
"More often than I thought, I go back to refer to it for nearly anything algorithm-related; time complexity of common algorithms, linear programming, NP-Completeness, Dynamic Programming."
"The best book in algorithms, its kinda like a bible as far as algorithms is concerned."
"It is a very nice book, but sometimes you can find a simpler description/explanation of some algorithms."
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Best Combinatorics

The Algorithm Design Manual
Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. ....The most comprehensive guide to designing practical and efficient algorithms!.... The Algorithm Design Manual, Second Edition. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. Written by a well-known algorithms researcher who received the IEEE Computer Science and Engineering Teaching Award, this new edition of The Algorithm Design Manual is an essential learning tool for students needing a solid grounding in algorithms, as well as a special text/reference for professionals who need an authoritative and insightful guide.
Reviews
"Great book, very detailed explanations of the most often used algorithms."
"Clear, concise, C style coding."
"This is a great book."
"Good book for beginners."
"Probably the best book that I own on Algorithms and Data Structures."
"An excellent book for the software developer interview preparation."
"The content of the book is nice."
"For those familiar with standard algorithms book, "Introduction to Algorithms" this book is probably equally as good without being at technical or mathematical."
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Best Genetic Algorithms

Elements of Programming Interviews in Python: The Insiders' Guide
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
"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!"
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Best Computer Simulation

Introduction to Algorithms (Eastern Economy Edition)
Each chapter is relatively selfcontained and presents an algorithm, a design technique, an application area, or a related topic. The algorithms are described and designed in a manner to be readable by anyone who has done a little programming. "As an educator and researcher in the field of algorithms for over two decades, I can unequivocally say that the Cormen et al book is the best textbook that I have ever seen on this subject. "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
"It is a very nice book, but sometimes you can find a simpler description/explanation of some algorithms."
"Now 8 years later, I bought the third edition to renew these knowledge."
"However, it's still an introduction to algorithms, although it's already hard for most of averaged students."
"I love this book."
"This textbook isn't just a textbook for an algorithms class."
"Gives complete and deep explanation on topics covered."
"This type of material is easier to read on a wide screen."
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Best Computer Systems Analysis & Design

Head First Design Patterns: A Brain-Friendly Guide
By the time you finish this book, you’ll be able to take advantage of the best design practices and experiences of those who have fought the beast of software design and triumphed. Eric Freeman recently ended nearly a decade as a media company executive, having held the position of CTO of Disney Online & Disney.com at The Walt Disney Company. More recently, she's been a master trainer for Sun Microsystems, teaching Sun's Java instructors how to teach the latest technologies to customers, and a lead developer of several Sun certification exams.
Reviews
"a nice intro to design patterns."
"I love these Head First books."
"I've always preferred and loved the idea of fun and learn being together, and this book does exactly that, it's a book so easy to read that helps you to keep reading, and invites you to actually do the excercises, and they look fun to do."
"Fun book."
"It presents exactly what you need to know in an easy and fun to read format, making it much less of a textbook and more of a "Hey look at all this cool stuff you can do with software!""
"While GOF book covers more patterns, it's not as nearly as much fun to read as Head First Design Patterns. Bottom line: - I definitely recommend this book to any junior developer who wants to get familiar with Design Patterns. - Experienced developers will skip quite a few pages (like I did), yet it's still a good read."
"Great book, I should have read it years ago."
"This book is definitely not the patterns Nirvana, and it may not make you the patterns guru, but it sure is a great book, extremely well written to welcome the beginner to the world of patterns. Once I master this book and practice the patterns, I am sure I will be able to move to the next level and maybe I will be better able to understand the GOF bible which I learn is a must read for any serious techie!"
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Best Computer Programming Structured Design

Algorithms (4th Edition)
This fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms is the leading textbook on algorithms today and is widely used in colleges and universities worldwide. The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. Robert Sedgewick has been a Professor of Computer Science at Princeton University since 1985, where he was the founding Chairman of the Department of Computer Science.
Reviews
"Pure, elegant coding."
"Great book on algorithms: the author explains basics, then goes dipper into the topic."
"Great book!!"
"Indispensable algorithms reference and textbook."
"I really enjoy reading this book."
"I thought I still had it, so when I find I needed the C version for a graduate class (this has since been upgraded to Algorithms in C++) I decided to sve beaucoup bucks in getting a used version."
"Every programmer should have the hard copy of this book in his/her library."
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Best Discrete Mathematics

Discrete Mathematics with Applications
Susanna Epp's DISCRETE MATHEMATICS WITH APPLICATIONS, FOURTH EDITION provides a clear introduction to discrete mathematics.
Reviews
"This book is great!"
"If you wanted to setup a good base for going towards any mathematically rigorous Computer Science book - then you must read this - its very systematic, exercises are designed in a way that makes you understand concepts really well."
"The only math book that I can say that for."
"I like this book."
"Ms. Epp explains things very clearly and thoroughly so that you don't get lost, and illustrates how the math is useful in areas of computational theory/computer science."
"It's been a couple of decades and I wanted a refresher on discrete math foundations."
"Be very careful when buying this book and others used online, The book was listed as "Acceptable" but the binding was almost completely off and quite a few pages were folded in or had a fair amount of ink on them."
"Great Book, didnt even have to go to class because the book is so well written."
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Best Stochastic Modeling

Doing Data Science: Straight Talk from the Frontline
Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course. Rachel Schutt is the Senior Vice President for Data Science at News Corp. She earned a PhD in Statistics from Columbia University, and was a statistician at Google Research for several years. She holds several pending patents based on her work at Google, where she helped build user-facing products by prototyping algorithms and building models to understand user behavior.
Reviews
"The book Doing Data Science not only explains what data science is but also provides a broad overview of methods and techniques that one must master in order to call one self a data scientist. However it is not to be considered as a text book about data science but more as a broad introduction to a number of topics in data science. I had for some time been looking for a book that could be used as a follow-up reading on topics in data science. The book begins with a chapter about what data science is all about is followed by four chapters on topics like statistical inference, explanatory data analysis, various machine learning algorithms, linear and logistic regression, and Naive Bayes. I really enjoyed the examination of time stamped data, the Kaggle Model, feature selection, and case-attribute data versus social network data. Data visualization is an integral part of data science for communication results. Topics that I did not found covered in any other book about data science. However the chapter about epidemiology is not about using data science in epidemiology but 'just' about using data science to evaluate the methods used in epidemiology. Personally I would prefer more details about the actual data science topics like e.g. extracting meaning from data and social network analysis and less focus on math. I really like the idea about having a lot of different people present various topics in data science and the book is well written and contains lots of useful resources for further studies of data science."
"Great text that provides a very informative overview of topics in Data Science."
"The books is fairly dated, a lot of the exercises have broken links/outdated code."
"The book is well written and provides good insights into how to form a foundational core to further one's education and experience in data analysis and visualization."
"However, the presentation of material makes it difficult for a student to quickly follow."
"I make my living working with businesses to help them build their analytic capabilities in sales and marketing, by working on real opportunities and generalizing lessons from specific experiences and results. But what I have learned is that if you push these past use as points of departure, and force them as points of arrival, results and learning suffer."
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