The most recommended books on algorithms

This was my favorite book when I started my career. It talks about how information is processed, in an intelligent way, in the internet age. It acts as a tutorial to teach developers how to code our own ML programs, from online dating services, to document analyzer, and search engine. The author did an excellent job of explaining abstract ML algorithms with clear examples. His coding style in Python reads clearly, which makes the book more beginner-friendly.

Don’t get disappointed when you know this book is more than a decade old. It was a visionary book back in the day and it is still relevant today.

How do we know whether an algorithm is correct? While intuition is helpful, for tricky algorithms nothing beats the formal proof. But I don’t want a proof for proof’s sake: I want it to deepen my understanding of the algorithm. The proofs in this book series are the best I’ve seen: they are self-contained, described step by step, and serve to sharpen your understanding of what the algorithm is really doing. Couple that fact with the self-check questions, exercises with solutions, and associated video lectures, and what we have here is a wonderful resource for the motivated algorithms learner.

Yes, it’s a textbook, albeit a particularly well-written one. You may already have it on your shelf, if you’ve taken a programming class or two.

I’m way too old to have used CLRS as a textbook, though! For me, it’s an effectively bottomless collection of neat little ideas—an easy-to-describe problem, then a series of increasingly clever ways to solve that problem. How often do I end up using one of those algorithms? Not very often! But every time I read the description of an algorithm, I get a nugget of pure joy from the “aha” moment when I first understand how it works.

Billy Bragg has long been my favourite musician. I have all his albums including his 1986 offering, Talking With the Taxman About Poetry.

I included this book because it is about the importance of accountability. This is an important concept for managing public money. The wish for our governments to operate in an honest and fair way requires there being a way to judge their performance. This means that the politicians, civil servants, and everyone else who is involved in government must be willing to be accountable for what they do, and also for what they omit to do. When I teach public financial management I say to my students that if they do not want to be accountable for their actions they should not work in public service.

The most important unanswered question in computer science has a huge public relations problem. Back in the 1970s, this question became known as “P=NP?”—and who could write an exciting book about that? Luckily for us, Lance Fortnow can. As one of the world’s foremost experts on P-vs-NP, he takes us on a wild and truly accessible ride through the most important question about computing. I’ve seen many attempts at making “P=NP?” accessible/understandable/intriguing for non-experts. But Fortnow nails it like nobody else, reformulating P-vs-NP as a search for one of the golden tickets in Charlie and the Chocolate Factory. (Which is another one of my favorite books, even though it’s not going to make it onto this list about algorithms.)

In Book Funnels & Amazon Ads, Alex draws from his experience of working with hundreds of authors. He delves into Amazon Advertising and reveals how to leverage this unique opportunity to your advantage. Amazon ads can be very effective for authors but you need to educate yourself before diving in. There is too much to know to just ‘wing it.’ This book was written by a person who is first a techie guy and understands Amazon algorithms like you and I will never comprehend.

Follow Alex’s advice and use Amazon ads.

Peter Winkler is famous for his collections of counterintuitive puzzles. Thousands of people, including me, have spent many sleepless nights trying to understand the mysteries in these puzzles, for which, I am forever grateful.

Haunting puzzles in the book include hats and infinity, all right or all wrong, comparing numbers version 1/2, wild guess, laser gun, precarious picture, names in boxes, sleeping beauty, and dot-town exodus.

Most puzzle books exclude counterintuitive puzzles for unknown reasons. So, many people incorrectly assume that counterintuitive puzzles are majorly found in paradoxes. Peter Winkler in this book shows that counterintuition can come from either puzzles or solutions or both, and they need not come from paradoxes alone.

Finally, reading Winkler's statements is an absolute delight due to its enjoyable and entertaining nature.

This is the book that started it all for me… and I think it holds up just fine today. I see value in confronting the old Pascal code every so often: it’s a reminder of how little we need in order to make our algorithms fast, and how much is happening behind the scenes by our modern programming languages. To this day this book has some of my favourite presentations of Dijkstra’s Algorithm and sorting.

Richard’s authoritative leading textbook excellently describes the whole field of computer vision. It starts with the sensor, moves to image formation followed by feature extraction and grouping, and then by vision analysis. It’s pragmatic too, with excellent descriptions of applications. And there is a ton of support material. This is a mega textbook describing the whole field of computer vision.

This is one of the first books in the entire puzzles literature that gave multiple detailed solutions to several beautiful mathematical puzzles.

Some of today's most famous puzzles were either popularized or introduced in this book. For example, truck in the desert, start of the snow, the rookie electrician, hole in a sphere, captivating problem in navigation, the hunter and his dog, the counterfeit coin, and common birthdays.

This book with its multiple-solutions feature taught me that we should never stop searching for more solutions as there can always be a better solution. Furthermore, when 1- or 2-paragraph solutions were the norm, this book illustrated the beauty of having multi-page detailed solutions.

Interestingly, this book is a crowd-written book as most of the puzzles and solutions presented in this book are contributed by readers of a magazine. This implies that it is possible to write great crowd-written books.

This is the definitive book series on algorithms and the core of computer programming.

Unlike most such books, Knuth is a real programmer, deep into the details of the craft, to the point of creating his own assembler language and typesetting generation system. It’s partly the substance of the algorithms and their analysis, but even more is the way he models a way of thinking about and solving complexity that makes this a must-read series.

As I write these lines, artificial intelligence (AI) is getting a lot of attention.

This is largely due to ChatGpt recently bursting onto the scene. But even before ChatGpt began making its mark, AI was often in the news. Some have expressed worry that it will take our jobs, others that it will reinforce systemic oppression by making racially or otherwise discriminatory decisions, and some have even voiced concerns that one day a superintelligent AI might pose an existential threat to humanity.

In the midst of all this, what might get lost is what AI is, what it's capable of doing, and what its limitations are. Wenger's book is intended to address all of these questions. It manages to do so in a way which goes into some of the mathematics of AI systems and yet remain accessible to a lay audience.

After laying out the technical aspects of AI,… show more.

A dystopian future that's so close to now it made me squeal. Mega-techcorp Beetle is in charge of – well, basically, everything: CCTV, your household appliances, virtual assistants, robot cops, predicting the future... Only one problem: individual human cussedness/autonomy – the elusive variable Zed – keeps gumming up the algorithms and really shouldn't exist. I love the way the Beetle founder and his assiduous employees just can't see why their beautifully controlled society is quietly driving its citizens nuts with despair. Apart from my constant horror-laughter of embarrassed recognition, there's a scene involving robot hospital orderlies which is one of the most chilling things I have ever read.  Do we really want a future like this?

For an overview book that focuses on intuition—a book that is intentionally designed to evade formality—to make my list, it has to be really, really good. This one is. I appreciate the inclusion of real code in multiple programming languages and the step-by-step traces of algorithms. I appreciate the care taken with the Big O material and the way that abstract data types are introduced. This is one of very few books whose recursion material I like—the ‘napkin’ approach to recursion is wonderfully done.  

Adding perspective puzzled artists in the fourteenth century; analysing perspective is integral to applied computer vision. You might have seen Hawkeye in action: the principles by which it works are explained superbly within this book. It was the first of its kind to set this analysis in a lucid and compelling format. Richard and Andrew’s text will be on researchers’ bookshelves for many years for its bedrock description of how we analyse three-dimensional scenes.

The building blocks of software are algorithms, so here our journey continues after you have established a deep understanding of programming languages.

Modern software is predominantly distributed, and since this book doesn't assume much it is the perfect introduction to algorithm analysis, concurrency, and distributed systems. And the best part is that you can just jump in and build these algorithms yourself.

This is a very short (of course!) introduction to cryptography, but it is masterful in its concise conveyance of all that really matters on this topic. I have no hesitation in admitting a close relationship with both authors, but most particularly Fred Piper, who was my doctoral supervisor. Fred has been a mentor throughout my professional life, and this book presents his take on the crucial components of modern cryptography, written for a general audience. I’ve seen this book in airport bookshops and thought `how cool – you can buy a book on cryptography that is written so well you could read it on a plane!’ I have now written two books about cryptography that are less short, and might need longer plane journeys, but Cryptography: A Very Short Introduction remains an inspiration to me.

Knuth is perhaps the true founder of Computer Science, who set out in the late 1960s to produce a seven-volume series of books containing all the foundations of the discipline.

Three volumes appeared by 1973, after which he got distracted by many other things, and the promised volumes seemed destined never to emerge. But Knuth finished Volume 4A in 2011, after a lapse of 35 years. And then, in the Fall of 2022, at the age of 84, he published the 712-page Volume 4B: Combinatorial Algorithms Part II!

There is nothing in the world like a Knuth book. He has a unique way of looking at the world and an unrivaled sense of detail and humor. He goes deeper down rabbit holes than any man alive, and you come out smarter and with a sense of wonder that such books really exist.

Volume 4B is dedicated to combinatorial search algorithms,… show more.

This is a clever and highly readable guide to the brave new world of algorithms: what they are, how they work, and their strengths and weaknesses. It’s packed with stories and vivid examples, but Dr Fry is a serious mathematician and when it comes to the crunch she is well able to show it with clear and rigorous analysis.

Remember How to Lie With Statistics? Here is: How to abuse big data. And how to stop the abuse.

O’Neil is a good corrective for my own habit of seeing all sides. A former math professor and quant, she is harsh on AI because it systematically punishes the vulnerable and impoverished – and because companies resist change and manipulate the laws to keep their profits.

“Right now, the burden of proof is on us,” she told Juliette and me in an interview, “to prove that these algorithms harm us. I want that burden to be on the companies who profit from using them.” Weapons of Math Destruction argues that we can and should hold the perpetrators – including some of the world’s biggest tech companies – accountable.