### No bullshit linear algebra v2 release

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.

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. ### Linear algebra v2 beta release The No bullshit guide to linear algebra files on gumroad were updated. The book is now v2 beta 2, and scheduled for release in early January 2017. If you’re taking a linear algebra class this term, or need to know linear algebra for a more advanced class, this will be the best money you spend this semester. ### Why? Math is power. Specifically, the ability to use math models to describe real-world phenomenon and predict the future is a powerful general tool to add to you toolbox. Linear algebra has applications to many fields. In general, understanding basic math, and specifically functions of the form $f(x)=y$ like $x,x^2,x^3,x^n,e^x,\ln(x),\sin(x),\cos(x),\tan(x),\ldots$ opens many doors for mathematical modelling. Linear algebra is the study of linear transformations, or vector functions of the form $T(\vec{v}) = \vec{w}$. The linear transformations take vectors $\vec{v}$ as inputs and produce vectors $\vec{w}$ as outputs. Many real-world phenomena in computer science, physics, chemistry, biology, and many other fields can be modeled as vector quantities, so linear algebra has countless applications. Linear algebra is the vector extension to your math modelling toolbox. ### How? Everyone knows that math is useful, but people much rather leave the learning of math to other people, rather than learn math themselves. Most people imagine learning math is a difficult task, like carrying big bags of potatoes up a steep hill. Surely, such hard work is not for everyone, and we should delegate all the potato-carrying to experts in the field (mathematicians, scientists, and engineers). This way of thinking gave us a modern world where only a small portion of the world is math literate. Everyone else lives in ignorance and fear of all things mathematical. It doesn’t need to be this way. Everyone can learn math—even advanced math like linear algebra—if they follow a structured approach. Each section in the No bullshit guide to linear algebra follows the same recipe: • Motivation to trick readers into wanting to learn about the topic • Definitions of all quantities and variables relevant to the topic • Formulas: all the essential formulas associated with the topic are given • Examples that show how to use the formulas in different scenarios • Explanations about how the formulas are derived and how to understand them • Discussion about how the connections between this topic and other • Exercises to test your understanding of the concept • Links to web resources for further reading This structure allows to get all the important information across in the shortest amount of time. The reader is free to skim through superficially, or dig in an read all the explanations. The exercises help both students and self-learners test there understanding of the material. ### What? The No bullshit guide to linear algebra is a short textbook that covers all the standard topics of university-level linear algebra, and also discusses applications like machine learning, computer graphics, probability theory, and quantum mechanics. You can buy the eBook bundle here ($29, includes all future updates). The book is currently being edited, so it’s likely to see some further improvements to the chapters on applications, but the main material (that which will be on a an exam) is absolutely solid now.

@Students: get in touch with me if you’d like to be a “test subject” for the new  problem sets. I wrote 50+ pages of new problems and solutions for the book, and I could use your help to double-check the answers.

### Learning can be fun

I just read this excellent article Pragmatic Learning: It’s not “fun” on Roger Schank’s blog. It’s a very good post that calls bullshit on the “gamification” cargo cult which is widespread in the edtech and corporate training world. Just adding points, badges, and levels to a corporate training program that teaches you something boring is not going to suddenly make it fun. The author’s main observation is that forced learning is not fun and we need not pretend it is. Consider an employer who wants their employees to know X because it is required by law, or a bunch of students forced to learn Y or else they’ll fail. These “forced” trainings are not fun, and gamifying them is akin to putting lipstick on a pig.

Instead of gamification, the author suggests learner’s experience should focus more on things like:

• Getting away from the one-size fits all approach:

Courses need not be administered to multitudes. One can have a course that is for one person only and can be used when needed. […]

• The use of simulators
• Enable students to collaborate with peers who are learning the same thing
• Have human teachers (tutors) available to help
• Enable “learn by doing” experiences:

[…] real autonomous, motivated, learning happens when you are in the middle of doing something, and questions arise in your mind about it.

• Provide training in a “just in time”(JIT) manner, e.g. provide training on X right before the student will need to do X.

I highly recommend you read the article because the above summary hardly does it justice. I agree with 90% of the observations in this article, but I have some comments and observations of my own to add below the fold.

### No bullshit guide to programming

How does one learn to code? Students in computer science and software engineering will have a few first-year programming courses, with the first one introducing basics like variables, control flow, and loops. Autodidact programmers probably started with a tutorial somewhere, but eventually got a book on the subject. Regardless of the learner’s path, we’re talking about a book that teaches “the basics.”

1. Fundamentals
1. math review (numbers, variables, functions, multi-step procedures)
2. syntax and new type of objects (variables, functions, algorithms, int, float, list, dictionary, objects)
2. Programming basics
1. Expressions
2. Functions
3. Control flow
1. If elif else
2. Loops
3. Structure of programs
1. modules
2. libraries
3. frameworks
4. Algorithms
1. Binary search algorithm
2. Sorting algorithms
3. Graph algorithms
4. Numeric algorithms
5. Optimization algorithms
5. Applications
1. Fancy scientific calculations made easy (SymPy, numpy)
2. Automate info. processing tasks (bash scripting)
3. Generating reporting and useful analytics from data (pandas)
4. Creating websites (Django)

It’s not the standard set of topics for the “COMP101 textbook” category,  but I bet with some thought put into it, it can be made to contain most of the material for a first-year coding class. We just godda make sure that profs will have enough to support teaching their class. Best of all it could all probably fit in 300 pages, and retail under $40. It could be even thinner, but would be better to have lots of exercises. I’m thinking about this today because I was visiting McGill and had the chance to talk with the prof who taught my first-year programming course and we somehow got to the topic of textbooks. She remembered the computer science textbook she learned from, and described it as being very thin. So it can definitely be done. The book described above doesn’t exist yet, but if you leave comments below telling me you want it, it will move up in the priority list… ### Annual general update It’s May. Winter is done now, so it’s time for spring cleaning! In addition to cleaning your living space, Spring is also a good time to clean out the “project plans” and focus on one or two key goals for the summer. This is what I intend to do in this post. Read on to learn about the recent developments, and the strategic plan for Minireference Co. for the coming year. Since the LA book is finished, I will have more time now to focus on software projects and push forward all aspects of the business. Being in content-sprint-mode on LA applications for the past year really didn’t leave much time for updating the website, communicating with readers, twitter outreach, and developing sales and marketing channels in general. It’s like the business side of the company is asleep for one year. Business is going strong, but to grow to 10x current size we’ll need a good strategy. It’s time to extend the product line to Web, Mobile, ePub, and Kindle. It’s also time to develop new products like email courses, exercises, jupyter notebooks, youtube tutorials, and maybe even audio lessons. A younger version of me would try to do all of these at the same time, but now I know that technology for the sake of technology is an empty pursuit. (That being said, sometimes quick wins can be had using the right tech, so any project that can ship in less than a week is OK.) I need to think strategically, and also not think too much and focus on shipping. #### The big picture Let’s first figure out the overall mission. What do you want your readers to become? I want all my adult readers to become awesome at math. Also, I want all the analytically minded youth to be aware of the System. I want everyone to have affordable access to university-level science knowledge. Okay, so how do we do this? #### Content Writing books is a lot of work, but there is no way to avoid this. If I want to ensure a consistent high quality of explanations and the logical coherence of the lessons, I have to be involved with all the books. I don’t need to be the main author though—I can be the developmental editor. I think this is my true calling in life. Each book takes about two year to produce, so as long as it’s just me writing, Minireference Co. will always be on the flat part of the hockey stick growth graph. The best thing for growth right now is to find qualified authors that can help me scale to 10x current number of books in two years. Somewhere out there there is a chemist with years of tutoring experience who can write the No bullshit guide to chemistry in no time at all. Somewhere out there there is an economics grad student who can explain all the ideas from macro and micro economics in a single 200pp book. Same for differential equations (can be written either by a math student or an engineer, or a collaboration?). I definitely need a stats book too, written by a real statistician. Content TODOs: 1. Write pitch for authors along the lines of “Think you have a book in you? Join the Minireference Co. content team, and get paid to write about your favourite subject.” 2. Update website, adding a new /authors endpoint. 3. Think about revenue sharing models. Contractors? Royalties? Advance? Write contracts. 4. Write a white paper on self-publishing tools. Package and release LaTeX templates and ePub production scripts for use by other authors. 5. Develop scripts for publishing workflows based around text sources (md/tex), github repos, diffs, typo fixes, and multi-author collaboration. [BACKLOG] #### Distribution platforms Given the effort involved in producing educational content, it makes sense to distribute it as widely as possible. We need a multimedia approach. The print books are good. Distribution TODOs: 1. Create the split-versions of the first book for Kindle: No bullshit guide to math, No bullshit guide to mechanics, No bullshit guide to calculus. [June 2016] 2. Finalize LA book, and push it to Lulu, Amazon, and Ingram channels. [August 2016] 3. Release a iOS and Android apps with book content. Keep it simple: use a basic ListView for browsing the topics and WebViews (HTML+MathJax) for each topic. [Summer 2016] The above goals are easy to achieve and totally worth doing. The last thing you want to do in business is to waste time. Every week that I’m not on the kindle store means hundreds of dollars of unrealized sales. The LA book needs to ship ASAP too. People have been waiting, for so long. #### New products Books are good and all, but we need to think about the future. Will print book still be around 50 years from now? Maybe. But surely technology can play some role. Below are some product ideas that I plan to test in the coming years. 1. Email course. Adult learners who are learning math and physics on their own need a little structure—a series of emails to keep them on track with their studies. Imagine a sequence of 10 emails that walk you through the sections of a chapter. Each email can contain links to lessons, video tutorials, exercise sheets. 2. I’ve been experimenting with video tutorials and notebooks. I’m very impressed with the efficiency of teaching using jupyter notebooks and SymPy. I also like the “walkthrough” model of teaching, based on the book. But do the video lessons work? Are they effective at delivering the knowledge? Should they be at 1x, 1.5x, or 2x playback by default? 3. Mobile applications. Everything has to be mobile these days. There is an opportunity to reach a wider audience through the Google Play Store and the Apple App Store. The plan for this project is in two steps: MVP as a Free app (lessons, concept map, exercises) [DEMO] Introduce paid apps based on feedback and experience of the free app 4. EXERCIS. No learning is complete without putting the new knowledge into practice. That’s why I need to develop an exercises framework. It’s time I invested some dev efforts into this. I won’t be starting from scratch, but use khan-exercises or edX stack. I can offer it to readers either as a free bonus (incentive to buy book), or as part of the “deluxe” edition of the book. With the exercise framework packaged as a standalone JavaScript application, it can be distributed to students to use offline, or used from inside a WebView in the mobile applications. 5. STRUCTURE. For as far back as I can remember, I’ve been obsessed with building a graph-like structure to describe the connections between all subjects, topics, and concepts in science and math. Now’s the time to finally build it! Strictly speaking, the graph by itself is not a product but the base for other products. For example “a concept browser” could be used to help people orient themselves in any field. Also a “what to learn next” recommender system can be build based on the knowledge of prerequisite structure between concepts. These are all nice projects, but each of them requires a lot of development effort. I will need help. I could potentially try to pull it all off on my own, but it would be much faster to get interns to help me, or hire contractors. It’s not something I’m experienced with, but I think if I write solid specs for all these products, I could get external help. #### Marketing push With the two books in print (through lulu, amazons, Ingram) and digitally (gumroad, kindle), it’s now time to invest some cash and effort in a marketing campaign. A friend of mine who works in advertising recommended using a 30sec youtube video ad. Given a budget of \$20k for this, producing the video would take around \$10k and another \$10k would be used for the ads. If the video is good, such a campaign could lead to \\$20k in sales. And if ROI>0, then I should do it, right?

I should really have a presskit for the company, and reach out to the tech news outlets and the startup community. Surely there is some free publicity to be had. The general themes of expensive textbooks will surely receive attention. Not sure how to spin it, but it’s definitely worth investing into this now that v5.1 of the math book is solid, and once v1.0 of the linear algebra book comes out.
Exercise framework

I’m a little disappointed by the referral page I setup for Shoutly. It’s probably my fault for not putting more thought and effort into it. Despite this failure, I still think there is a lot of potential for a referral program when setup right. If I can reach one student in a class of 300 undergraduates and incentivize her to recommend the book to her classmates, then I’m golden. Giving her a cut of sales profits could be good, but maybe there are other ways too? What if she can setup a “discussion group” for her class, with a unique URL. She won’t be “pushing” the book directly, but setting up a community for her class. Then again, I’m sure there are facebook groups for this already.

I’ve got many other ideas brewing too, but I don’t want to spread myself too thin. Instead of hiring authors, I could focus on the publishing technology, content curation, and recommendations. I recently bought EZOER.COM which would be a nice home for such a project. The best part about OER is you can still sell the print book. You can’t charge a huge margin, but it’s not like I’m very extractive right now either.

So, lots of things for Summer 2016. I better move my desk closer to the coffee machine