100 books like Introduction to Classical and Quantum Computing

I like Prof. Cohen's book because it includes computational examples based on Python and NumPy to illustrate each concept. This is the way I like to think about linear algebra concepts.

Yes, it's important to understand the formulas and theoretical ideas, but applying linear algebra operations in the real world will always involve some computational platform and not pen and paper. This is the only book I know that shows readers the practical computational linear algebra in parallel with the theory.

The author provides computational notebooks for each chapter on GitHub, which makes it easy to explore all the material from a code-first computational perspective.

Prof. Strang has been teaching linear algebra at MIT for more than 60 years! This wealth of experience shines through in his book, which covers all the standard concepts using clear and concise explanations that have been polished through time and contain just the right amount of details.

The book is accompanied by a whole course of video lectures available through MIT OpenCourseWare or via YouTube. I learned a lot from Prof. Strang's approach to teaching; in particular, I appreciate the visualization of the fundamental theorem of linear algebra and his explanation of the matrix-vector product from the column picture and the row picture.

If you want to learn linear algebra, you can't go wrong with this classic.

In my opinion, Prof. Axler's book is the best way to learn the formal proofs of linear algebra theorems.

My undergraduate studies were in engineering, so I never learned the proofs. This is why I chose this book to solidify my understanding of the material; it didn't disappoint! Already, in the first few chapters, I learned new things about concepts that I thought I understood.

The book contains numerous exercises which were essential for the learning process. I went through the exercises with a group of friends, which helped me stay motivated. It wasn't easy, but all the time I invested in the proofs was rewarded by a solid understanding of the material.

I highly recommend this book as a second book on linear algebra.

This book has been a bit of an inspiration for me, and I use it regularly as a reference.

First of all, the content is complete and covers all the standard topics, including complete proofs. I like Heffron's book particularly because of the comprehensive exercises with complete worked solutions. It's hard to over-emphasize the importance of solving problems when learning, and this book has A LOT of them, which makes it an excellent choice for anyone learning on their own.

The author also provides lots of bonus material through his website, including slides, homework assignments, and a video lecture series. Last but not least, the entire book is released under an open license, allowing instructors to adapt and customize the material.

A simple (not perfect) test of whether you’re going to love this book: Just check out the author’s blog, called “shtetl-optimized”. The style is similar: sharp, funny, mixing professional theoretical Computer Science with broader takes.

I am still in the middle of the book, and nevertheless, I’m happy to recommend it. As an amateur with superficial CS knowledge, I am enjoying this introduction to classical complexity theory and the basic theory of quantum computation.

Aaronson’s distinctive style makes the ride all the more enjoyable. It’s neither a “real” textbook nor a pop-science book. It’s in a weird space somewhere in between, and I love it!

This masterful book goes one step further and presents a game-based analogy that goes a long way toward explaining how a quantum computer actually works. Working through the book, one gains an understanding of how qubits can be quantum entangled and how entanglement leads to computing tasks that could not be performed on an ordinary computer. Deceptively simple in appearance, the method leads you deep into the inner workings of quantum logic operations without realizing you are digesting some pretty advanced concepts. The author knows of what he writes, as his theoretical discoveries led to one of the world’s most ambitious quantum computing efforts.  

John Bell’s theorem about the unavoidability of what Einstein called “spooky action-at-a-distance” in quantum mechanics set off the second quantum revolution, leading to quantum computation, quantum cryptography, and quantum teleportation among other insights. This book collects Bell’s most important papers which range in style from professionally mathematical to popular and intuitive, so there is something for everyone. Beginners can start with “Quantum Mechanics for Cosmologists” or “Six Possible Worlds of Quantum Mechanics” or “Bertlmann’s Socks and the Nature of Reality” or “La Nouvelle Cuisine”. Experts can learn from “Against ‘Measurement’”. People interested in the mathematical details can find them, and people scared by math can largely avoid them.

Now we are getting to the modern era, where physics meets computing in ways never dreamed of by the founders of quantum physics. Seth Lloyd is a professor at MIT and one of the first to prove that quantum theory admits the possibility of building computers on wholly quantum foundations. He is also one of the most creative and engaging writers on the subject. His main message is that information is the basis of all things physical. From quantum bits or qubits to cosmology, this book has it all, and is written in a highly accessible way. Not a single equation can be found. 

Ignatius’s most recent novel is in many respects a mashup of books no. 1 and 2 on this list: terrific storytelling and the latest spy recent tech: You’ll conclude that it’s just a matter of time until “bad actors” (spy speak for “bad guys”) can hack your brain. At the same time, you’ll enjoy the story.

The fields of Psychology, Economics, and Biology are well-known for offering interesting and informative introductory courses that provide a doorway into the area for budding scientists but also essential background knowledge appropriate for any educated person.

In Computer Science, we don't really do things that way. I wanted to offer a new kind of Computer Science introductory course that laid out the coolest ideas we have to offer along with compelling descriptions of why they matter.

I ended up using this book as the required reading in the class I built because it tells a personal, moving story while taking the reader from the nuts and bolts of bits and bytes all the way up to cutting-edge ideas surrounding artificial intelligence. It's a great read! Plus, it's short so I thought I could get my students to actually finish it.