Best Computer Science
And as such, I know what it's like to be asked to whip up brilliant algorithms on the spot and then write flawless code on a whiteboard. Learn how to uncover the hints and hidden details in a question, discover how to break down a problem into manageable chunks, develop techniques to unstick yourself when stuck, learn (or re-learn) core computer science concepts, and practice on 189 interview questions and solutions. Extensive coverage of essential topics, such as big O time, data structures, and core algorithms. At Google, she interviewed hundreds of software engineers and evaluated thousands of hiring packets on the hiring committee.
Reviews
Find Best Price at Amazon"The DP solutions in this book are not actually tabular DP formulations--I recommend looking at the problems here http://people.cs.clemson.edu/~bcdean/dp_practice/ (Brian Dean's Dynamic Programming Practice Problems)."
"I got several offers and without doubt this book helped. The specific coding questions that I would have failed outright on had I not read the book include: breadth first search/shortest path, fundamentals of hash tables, and recursion (fibonacci)."
"Like this book, the material very well structured, with real life examples."
"Good paper quality, great questions organized into exercises covering most important basics like Data structures, programming languages, problem approach etc."
"The afternoon before I interviewed with Amazon for a scientist role, the HR said you should prepare for data structure and algorithm."
"I did many other things to prepare besides using this book, but I nailed my interviews and got a great offer so I can't complain!"
"I've been writing software for a long time, and I'm competent at my job. Because the presence of books like these create a vicious cycle: prep book gets written; interviewees study/memorize answers; interviewers make questions "harder" to compensate; new book gets written! The grinder continues to turn, and whereas ten years ago you could get a good job with some string or linked-list manipulation questions, now you've got people who consider whiteboard coding of topcoder elite questions to be the baseline measurement of programmer competency. You'll even run into lazy interviewers who take questions directly from this book, which is the ultimate in stupidity: if "good" candidates have prepared from the book, and you ask questions directly from the book, what are you really accomplishing, other than a test of memorization skills? I've seen it myself."
Explore the machine learning landscape, particularly neural nets Use scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets Apply practical code examples without acquiring excessive machine learning theory or algorithm details.
Reviews
Find Best Price at Amazon"I got this book for the deep learning portion (about half of the overall book length), and was shocked at the clarity of the conceptual explanations and code implementations."
"Even though I come from a strong theoretical background, I have to say one must do hands on tinkering to be able to solve one's own problem successfully. There are pieces of information hard to find somewhere else, and I have spent hundreds to thousands to attend workshops. I was hoping Keras, a high level api that enables fast experiments, is covered."
"Great book, takes a while to get going, but shows some excellent uses of scikit learn."
"Book content is very up-to-date and offers great hands-on experience."
"Great Book, well explained a lot of good examples, one of those books that the more times you read it , the more you profit from it."
"The choice to start with Scikit-Learn was interesting, but makes sense on some level while he's introducing the more basic machine learning concepts. Simple machine learning techniques like logistic regression, data conditioning, dealing with training, validation, test set. Straightforward setup instructions, pretty intelligible explanation of the basic concepts (variables, placeholders, layers, etc.). The example code is quite good, and the notebooks are quite complete and seem to work well, with maybe a few tweaks and additional setup for some. Even just having a section on reinforcement learning is very rare in a book of this style, and Geron's samples and explanations are really solid."
"As with most technical books, it depends on where in the learning curve you are."
While consumers today are camping outside of an Apple store waiting to be one of the first to score a new Apple Watch or iPhone, the next generation of wearables will be able to predict if we're likely to have a heart attack and recommend a course of action. Following on from the Industrial or Machine Age, the Space Age and the Digital Age, the Augmented Age will be based on four key disruptive themes - Artificial Intelligence, Experience Design, Smart Infrastructure, and HealthTech. In a crowded field of prognosticators, Brett King stands out for his clearly articulated vision of how technology is changing who we are.”. — Michael J. Casey, Author of The Age of Cryptocurrency: How Bitcoin and Digital Money are Challenging the Global Economic Order. Brett King’s Augmented is a roadmap of the biggest changes and the most disruptive technologies we’ll need to navigate to get there.”. - David Bach, New York Times Bestselling Author.
Reviews
Find Best Price at Amazon"Great work BK, this looks like a real game changer in the way people will see their future and the way we will live in the very near future."
"The forethought and attention to detail regarding not only the current changes but future expectations is very well researched."
"This book paints a compelling version of our mankind’s future as it relates to technology."
"Though, this book is so good that I thought that I would take 10 seconds to write a review."
"Powerful."
"In this excellent book, he writes about how innovation and technology will affect almost every other aspects of life as well."
"The book is an excellent starting point for those wishing to learn about forthcoming technological changes and their social impact."
"A great book taking you from the 1900 till future detailing technology advancement .. A must read for all 👍."
Best AI & Machine Learning
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. (Geoffrey Hinton FRS, Emeritus Professor, University of Toronto; Distinguished Research Scientist, Google). Deep learning has taken the world of technology by storm since the beginning of the decade. (Yann LeCun, Director of AI Research, Facebook; Silver Professor of Computer Science, Data Science, and Neuroscience, New York University). [T]he AI bible... the text should be mandatory reading by all data scientists and machine learning practitioners to get a proper foothold in this rapidly growing area of next-gen technology.
Reviews
Find Best Price at Amazon"Because this book also makes very clear - is completely honest - that neural networks are a 'folk' technology (though they do not use those words): Neural networks work (in fact they work unbelievably well - at least, as Geoffrey Hinton himself has remarked, given unbelievably powerful computers), but the underlying theory is very limited and there is no reason to think that it will become less limited, and the lack of a theory means that there is no convincing 'gradient', to use an appropriate metaphor, for future development."
"The text does a very good job of informing the reader what has been done and was is being done for neural networks."
"Excellent overview."
"Great (and a very timely & relevant) book on this exciting and cutting edge domain."
"I am surprised by how poorly written this book is. I do not wish to speculate on the reason for this but it does sometimes does occur with. a first book in an important area or when dealing with pioneer authors with a cult following. More than half of this book reads like a bibliographic notes section of a book, and the authors seem. to be have no understanding of the didactic intention of a textbook (beyond a collation or importance sampling. of various topics). If you don't know linear algebra already, you cannot really hope to follow. anything (especially in the way the book is written). As a practical matter, Part I of the book is mostly redundant/off-topic for a neural network book. (containing linear algebra, probability, and so on). and Part III is written in a superficial way--so only a third of the book is remotely useful. It is understood that any machine learning book would have some mathematical sophistication, but the. main problem is caused by a lack of concern on part of the authors in promoting readability and an inability to. put themselves in reader shoes (surprisingly enough, some defensive responses to negative reviews tend to place. blame on math-phobic readers). A large part of the book (including restricted Boltzmann machines). is so tightly integrated with Probabilistic Graphical models (PGM), so that it loses its neural network focus. This portion is also in the latter part of the book that is written in a rather superficial way and. therefore it implicitly creates another prerequisite of being very used to PGM (sort-of knowing it wouldn't be enough). On the other hand, the PGM-heavy approach implicitly. increases the pre-requisites to include an even more advanced machine learning topic than neural networks. (with a 1200+ page book of its own). The book is an example of the fact that a first book in an important area with the name of. a pioneer author in it is not necessarily a qualification for being considered a good book."
"So…). If it’s for the people who want to get started with deep learning, it’s completely off topic, since it presents the mathematical nitty-gritty of the deep learning algorithms without mentioning any specifics of how to train a convo-net for example. If you’re really interested in Math behind Deep Learning out of curiousity (perhaps you’re a mathematician who wants to know what this deep learning thing is all about) perhaps this is a book for you."
Best Bioinformatics
This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. Almost all of the chapters are revised.… The Material is nicely reorganized and repackaged, with the general layout being the same as that of the first edition.… If you bought the first edition, I suggest that you buy the second editon for maximum effect, and if you haven’t, then I still strongly recommend you have this book at your desk. … the book may also be of interest to a theoretically inclined reader looking for an entry point to the area and wanting to get an initial understanding of which mathematical issues are relevant in relation to practice. … this is a welcome update to an already fine book, which will surely reinforce its status as a reference.” (Gilles Blanchard, Mathematical Reviews, Issue 2012 d). You can flip the book open to any page, read a sentence or two and be hooked for the next hour or so.” (Peter Rabinovitch, The Mathematical Association of America, May, 2012).
Reviews
Find Best Price at Amazon"In addition to having excellent and correct mathematical derivations of important algorithms The Elements of Statistical Learning is fairly unique in that it actually uses the math to accomplish big things. This hard use of isomorphism allows amazing results such as Figure 3.15 (which shows how Least Angle Regression differs from Lasso regression, not just in algorithm description or history: but by picking different models from the same data) and section 3.5.2 (which can separate Partial Least Squares' design CLAIM of fixing the x-dominance found in principle components analysis from how effective it actually is as fixing such problems). Unlike some lesser machine learning books the math is not there for appearances or mere intimidating typesetting: it is there to allow the authors to organize many methods into a smaller number of consistent themes."
"A good book in this area."
"While no book I have seen covers every data mining methodology available, this one has the strongest coverage I have seen in additive models, non-linear regression, and CART/MART (regression/classification trees)."
"Good book, help me build a systematic knowledge on statistics and machine learning. Of course, you may need some basic knowledge before reading it if you are novice."
"This book is basically the bible for statistical learning."
"This book is an excellent survey of the huge area of statistics / computer science called statistical learning."
"I'm a machine learning person, and this book provides pretty thorough state-of-art and up-to-date (relatively well) summary of statistical methods being used in lots of pattern classification fields."
"I have a PhD in Math and more particularly stochastic processes and everytime I open this book I can't quite understand what the content is."
Best Computer Simulation
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
Find Best Price at Amazon"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."
Best Cybernetics
In the years following her role as the lead author of the international bestseller, Limits to Growth ―the first book to show the consequences of unchecked growth on a finite planet― Donella Meadows remained a pioneer of environmental and social analysis until her untimely death in 2001. Just before her death, scientist, farmer and leading environmentalist Meadows (1941-2001) completed an updated, 30th anniversary edition of her influential 1972 environmental call to action, Limits to Growth , as well as a draft of this book, in which she explains the methodology-systems analysis-she used in her ground-breaking work, and how it can be implemented for large-scale and individual problem solving. An invaluable companion piece to Limits to Growth , this is also a useful standalone overview of systems-based problem solving, "a simple book about a complex world" graced by the wisdom of a profound thinker committed to "shaping a better future. "Dana Meadows' exposition in this book exhibits a degree of clarity and simplicity that can only be attained by one who profoundly and honestly understands the subject at hand--in this case systems modeling. This is modestly called a primer, and indeed it is, but unlike most books with that title, this one quickly takes one from the elementary into deep systems thinking about issues as critical today as they were when Dana wrote these words. As the book moves from the 'mechanics' of systems dynamics to Dana's more philosophical perspective, we are treated to her inherent belief in human values that consider the good of all, and how much more effective considering the needs of others is likely to be in solving larger, complex problems. The universe and our society may be very complex and operate in counterintuitive, non-liner fashion, but following the insights of this book and applying them will provide for far more effective solutions to the challenges of a 7 billion person planet than current incremental, linear responses by governments, corporations and individuals." For her systems thinking included the expected things like recognizing patterns, connections, leverage points, feedback loops and also the human qualities of judgment, foresight, and kindness. To live sustainably on our planet, we must learn to understand human-environment interactions as complex systems marked by the impact of human actions, the prominence of nonlinear change, the importance of initial conditions, and the significance of emergent properties. "An inspiring sequel to Dana Meadows' lifetime of seminal contributions to systems thinking, this highly accessible book should be read by everyone concerned with the world's future and how we can make it as good as it possibly can be."
Reviews
Find Best Price at Amazon"Pros. * Easy, non-jargony language. * Helpful diagrams. * Diverse real-world examples make it relatable. Cons. * Would have liked some exercises to help think through some of the concepts in the diagrams (e.g. feedback flows). * Would have liked some more in-depth case studies where systems thinking was applied, what the challenges were, how cross-functional teams worked together, etc."
"If you can get past the occasional typo this book will leave you with insights that you will use every day of the rest of your life."
"Read the book (your library may have a copy), then write your own review!"
"Reach, interesting material delivered in easy to understand, easy to follow, easy to reference form."
"From lucid introduction to basic stock and flow models to deep meditations on the messiness of reality and the need to extend both attention and caring beyond the limits of the quantifiable, this book is by far the best introduction to system's thinking that I have every read."
"Observe and identify the boundaries and the interconnections between systems before taking decision and judgement."
"A very accessible introduction to Systems, with some great examples and anecdotes."
Best Human-Computer Interaction
An inventive blend of autobiography, science writing, philosophy and advice, this book tells the wild story of his personal and professional life as a scientist, from his childhood in the UFO territory of New Mexico, to the loss of his mother, the founding of the first start-up, and finally becoming a world-renowned technological guru. His style is wonderfully discursive, reflecting his wide range of interests and experiences.”. ―Emily Parker, The Washington Post. “ Dawn of the New Everything spirits us back to a time when a plurality of ideas about what the Internet could be were still in play . “Jaron Lanier is both cheerleader and doomsayer in a highly personal story of virtual reality . a studied and nuanced interrogation of VR’s potential, as well as a gentle critique of what he sees as a failure of imagination when it comes to the medium’s current proponents.”. ― The Guardian. Integrating memoir, science writing, philosophical reflection, and down-to-earth advice, he reveals that virtual reality can clarify how the brain and the body connect to the world, giving us a deeper understanding of what it means to be human . This culturally significant title with its compelling personal narrative proves yet again that Lanier is a thinker whose work should be read and contemplated.”. ― Booklist. “Perhaps surprisingly for a book about the birth of virtual reality, this is a deeply human, highly personal, and beautifully told story .”. ―Dave Eggers, author of The Circle. It’s entirely unexpected and disarming to read about these concepts from an unabashedly subjective point of view. Not just for entertainment, but because Mr. Lanier has thoroughly convinced me that it’s the beginning of an enormous paradigm shift in the very way humans relate and communicate.”. ―Joseph Gordon-Levitt, actor and director. “The author is an evangelist for the good side of VR, which now offers insights into human perception and cognition that are forcing a radical re-evaluation of who we are. A spirited exploration of tech by a devotee who holds out the hope that bright things are just around the corner.”. ― Kirkus Reviews.
Reviews
Find Best Price at Amazon"(focused on digital networks) and You Are Not a Gadget: A Manifesto (focused on Web 2.0), this book lacks a focused narrative arc and is decidedly retrospective. Earlier works focused on challenging inherent assumptions and cautioned about potential consequences; this book, however, is a somewhat nostalgic take on the development of concepts of VR and has much more autobiographical tone (Lanier points out that most chapters begin from his boyhood and end around 1992; he does reference to many more developments since then, but the narrative arc is not a linear one nor complete, limiting a reader's ability to extrapolate). Interspersed with the 52 or so definitions of VR (some of which are just snarky, others filled with references that may be obscure for the casual reader), Lanier gives a autobiographical account of his growing up, learning to experiment with gadgets, and the general fascination of VR and mixed reality concepts."
"I have been waiting for this book to come out since I first started working in VR, and heard Jaron give a spellbinding talk in 1999."
"This is something a little different from Lanier's other writings."
"The book presents a biography as well as non-fiction texts – the life of a pioneer in the field of virtual reality, and ideas about this technology."
"Like: His views on AI and social media are an compelling and insightful, and worth reading."
"His appendix on Phenotriopic Programming was especially exciting."
"I'm not a techie and didn't have any particular desire to learn about the history of VR, yet I found myself pulled into the book and Mr. Lanier's world."
"Reality from the source of VR."
Best Information Theory
After an introduction to cryptography and data security, the authors explain the main techniques in modern cryptography, with chapters addressing stream ciphers, the Data Encryption Standard (DES) and 3DES, the Advanced Encryption Standard (AES), block ciphers, the RSA cryptosystem, public-key cryptosystems based on the discrete logarithm problem, elliptic-curve cryptography (ECC), digital signatures, hash functions, Message Authentication Codes (MACs), and methods for key establishment, including certificates and public-key infrastructure (PKI). Prof. Paar has taught cryptography for 15 years to engineering and computer science students in the US and in Europe, and he has taught many industrial practitioners at organizations such as Motorola, Philips and NASA. He has published extensively about his theoretical and industrial work through leading international conferences and journals, and he has taught many IT security and cryptography courses in industry.
Reviews
Find Best Price at Amazon"I work in information security and have a math background."
"Though I ended up not taking the class I read it anyways."
"I have same basic mathmatic knowledge, and good computer software skills, that's the requirment for readers."
"Excellent book."
"The math needed to understand the cryptographic topics is introduced as needed and explained clearly so that unfamiliar readers won't have any undue trouble understanding the material."
"Very good book which is easy to read and makes some subjects easier to understand."
"Actually I am taking professor Parr's Crypto course this semester."
"Easy to understand but a difficult subject for the novice trying to self teach."
Best Robotics
You'll also learn essential building techniques like how to use beams, gears, and connector blocks effectively in your own designs. The EXPLOR3R, a wheeled vehicle that uses sensors to navigate around a room and follow lines The FORMULA EV3 RACE CAR, a streamlined remote-controlled race car ANTY, a six-legged walking creature that adapts its behavior to its surroundings SK3TCHBOT, a robot that lets you play games on the EV3 screen The SNATCH3R, a robotic arm that can autonomously find, grab, lift, and move the infrared beacon LAVA R3X, a humanoid robot that walks and talks. Each chapter contains several short challenges, dubbed "discoveries," which are cleverly accompanied by a legend: whimsical gear wheels represent the estimated amount of building time; tiny Microsoft Windows-esque blocks show the expected level of programming expertise; and a small clock estimates the length of time it should take to solve the challenge. The size, advanced vocabulary, and organization of the book evokes a science or physics textbook, which is warranted due to the amount of complex and detailed programming information contained within.
Reviews
Find Best Price at Amazon"It is super for those who want to understand this Lego Robot machine and programming better."
"As to the educational version vs the home version..... The educational packs has all of the motors and sensors of the home version with two exceptions: the remote control sensor and related beacon. There may be a few add'l pieces that we'll need in the future to build all of the projects in this book, but we are 1/4 the way thru and haven't found them. The author has also kindly responded to specific questions (relating to education vs home versions), and has been quite helpful."
"Outstanding book I love the paper edition but also bought the Kindle edition too!"
"My grandson has built just about every project in the book and he loves it."
"I bought the book (and the Mindstorms kit) for my grandsons, but first I wanted to build one of the robots in the book and to do some programming for it in case I needed to help my grandsons with the versions they build."
"The book includes 132 practice modules spread throughout the chapters which allow for an iterative process of learning. My two sons and I (ages 9 and 11) are separately going through the book and practice/design modules with each of us tracking our progress on a tracking sheet."
"The book gives you all the information you need to understand the LabView environment and each of the basic programming blocks."
"Fantastic and thorough book."
Best Computer Systems Analysis & Design
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
Find Best Price at Amazon"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!"
Best Computer Performance Optimization
Having sold more than 2 million copies over its lifetime, How Computers Work is the definitive illustrated guide to the world of PCs and technology. Whether your interest is in business, gaming, digital photography, entertainment, communications, or security, you’ll learn how computing is evolving the way you live. Only the accomplished and award-winning team of writer Ron White and artist Tim Downs has the unique ability to meld descriptive text with one-of-a-kind visuals to fully explain how the electronic gear we depend on every day is made possible. Ron White has been writing How Computers Work for 20 years, during which time he’s also been executive editor at PC Computing magazine, BYTE.com, and groovyPost.com.
Reviews
Find Best Price at Amazon"I have used this book series since 1999 to better explain computers and networks to beginning students and laypersons."
"This book gives 2 pages for each topic, and is great for me, or for a curious person just wanting to learn more about computers."
"When i first pick this book i expect to have a book with some nice pictures about how computers works, now that i{m reading the book i have to say that i become adicted to it."
"Great book if you want to learn about computer and computer programming, it lets you understand how things work and how you can do this stuff yourself."
"It is so easy to forget how technology evolved and the many amazing small advances that contributed to it."
"Great book with many neat illustrations."
"coming in December), but the quality of the kindle version is nowhere near to that of the printed version."
Best TCP-IP
The book's visual approach makes it easy for students to learn about and understand the concepts involved in this rapidly developing field. Behrouz A. Forouzan a Professor at DeAnza College, where they are involved in the development of courses for Computer Information Systems.
Reviews
Find Best Price at Amazon"Used this book for a class."
"Rented this book."
"Just as advertised and shipped quickly!"
"Despite some grammatical flaws, the book provides good information for the reader who wants to know about the "nitty-gritty" details of networking."
"Exactly what I wanted and expected, and the product got to my house quickly."
"In order to really learn and understand computer networks this book should accompany other acceptable books as well."
"This book has some good explanations of current networking technology."
"Good textbook, this was the text for TCP/IP class at University of Denver."
Best Programming 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 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."