The most recommended books on algorithms

This multi-volume book is, for me, a masterpiece that goes far beyond just coding or algorithms or data structures, and serves as a profound exploration of algorithmic thinking and computer science's theoretical foundations, going deeply into the performance of algorithms and the behavior of data structures.

Knuth's meticulous approach, coupled with his clear and engaging prose (with occasional touches of humor) clearly explains complex concepts, and shows a deep understanding of the artistry inherent in solving computational problems.

Bill Gates said that anybody who went through all its volumes would get a job at his company, and I surely agree! I would recommend this book both for novice or seasoned programmers, because you will always find invaluable insights in it.

This book came out a few months after the first edition of my book, and I remember being really frustrated because it added so many important ideas.

I still find its interrogation of interfaces and how they interact, open as different tabs, intriguing. Johnson focusses on how online TV functions within an internet ecosystem. This leads to interesting ideas about what TV distributed via the internet means.

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.)

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.

This book is essential in that it follows a systematic and scientific approach to software development, advocating for clarity in expressing algorithms, providing a rigorous framework for designing and reasoning about programs, and, fundamentally, always focusing on formal methods and mathematical techniques to ensure correctness and efficiency in programming code.

Most importantly, the book doesn’t just show you how to prove programs correct, but also teaches how to arrive from a definition to an efficient and correct solution, so I would recommend this to every developer.

Anany Levitin introduced me to algorithmics – my second love (my first love is mathematics), through his legendary algorithmics textbook. He was one of my superheroes in my young adult life and he got me addicted to algorithms. His book is my favorite because it is beautifully organized based on design techniques, well-written, and uses nice puzzles to teach algorithms.

Levitin went much deeper and wrote this book on algorithmic puzzles. This book is the first mainstream book in the puzzle literature that taught beautiful algorithmic puzzles via various algorithm technique techniques. Levitin claimed several mathematical puzzles as algorithmic focusing on aspects of the solutions that are automatable.

Elegant puzzles (with extensive references) in this book that I have enjoyed include missionaries and cannibals, bridge crossing, circle of lights, MU puzzle, turning on a light bulb, chameleons, poisoned wine, game of life, twelve coins, fifteen puzzle, hats with numbers, and… show more.

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.

This could be the first stop of your brand new machine learning journey. I personally like how the technical concept is translated into plain English – each chapter starts with a high-level overview of a ML algorithm or methodology, concise and clear, followed by lots of visual examples and real world scenarios. I can guarantee you won’t get lost halfway. The book focuses on getting you introduced to ML with minimal math. But if you want to grasp some more of math, the next book I recommend is waiting for you. 

Smalltalk is not as common or popular as it once was, but the influence its design had on programming is hard to overstate.

Reading this book has changed how I think about object orientation, and how I design systems, learning the patterns of Smalltalk makes it clear what object oriented design is really intended to achieve.

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.