The **NO BULLSHIT guide to LINEAR ALGEBRA** is finally ready. After two years of writing and two years of editing, the book is now complete! Thanks to all the feedback from readers and the amazing attention to detail of my editor Sandy Gordon, the first print release is very polished.

### Can I see a preview?

I’ve posted an extended preview of the book here (160 pages, PDF) so you can get a feel of what’s included. I tried to make the preview useful on its own: rather than showing only a few pages from the introduction, I’ve included the definitions from all the sections, which are the most important part of the book.

If you’re not interested in reading a whole book, but just want to see the graphical representation of all the linear algebra topics, I encourage you to check the concept maps here. If you’re looking for a quick refresher on linear algebra concepts, you can check the four-page linear algebra summary here.

### Why should I learn linear algebra?

Linear algebra is the foundation of science and engineering. Knowledge of linear algebra is a prerequisite for studying statistics, machine learning, computer graphics, signal processing, chemistry, economics, and quantum mechanics. Indeed, linear algebra offers a powerful toolbox for modelling the real world. All areas of advanced science and engineering make use of linear algebra models in one way or another. So essentially, you need to learn linear algebra if you want to do science.

### Why do I need *this* book?

There are many great books about linear algebra that exist out there[1,2,3]. The **NO BULLSHIT guide to LINEAR ALGEBRA** is special because of the concise, conversational tone it is written in, the prerequisites material it includes, and the numerous exciting applications of linear algebra it discusses. This book is the result of years of private tutoring, which makes the narrative feel much more like a conversation with a friend rather than a stuffy lecture. I know from experience that many adults don’t remember basic math topics like algebra, functions, and equations, so the book includes a comprehensive review chapter (Chapter 1) to make sure everyone is on board with the fundamentals.

The “main course” of the book (Chapters 2 through 6) consists of all the standard material covered in linear algebra courses with lots of examples, exercises, and practice problems with solutions.

The book concludes with three “dessert” chapters that discuss applications of linear algebra. We start with applications to chemistry, economics, electrical engineering, graph theory, numerical optimization, cryptography, and signal processing (Chapter 7). Next we followup with a chapter on probability theory, Markov chains, and an exploration of Google’s PageRank algorithm (Chapter 8). The book concludes with a chapter that introduces the fundamental ideas of quantum mechanics and quantum computing (Chapter 9). Many of the topics covered in chapters 7, 8, and 9 are considered “advanced” or “graduate level,” but readers of the book who’ve gained a solid grasp of linear algebra concepts will be able to learn about these exciting applications with no problem at all.

### Where can I buy this book?

It depends on what you want. The eBook version costs $29 and is a pretty sweet deal since it comes with all future updates. But if you *really* want to learn the material, you should get the softcover print version, which is much better for focused learning, and costs about the same: \$39 – 20% off = \$31. If money isn’t a constraint for you right now, you should get the hardcover, which is printed on larger paper and has a construction that will last for decades.

Regardless of your choice of medium, you’ll be getting the same high quality book that will introduce you to the wonderful subject of linear algebra in the least intimidating way possible.