A reading list for the year ahead...

10 January 2019

Like many book lovers, I am guilty of something that is common enough that there is even a Japanese word for it: Tsundoku. That is, the habit of acquiring reading materials but letting them pile up in one’s home without reading them. In an attempt to combat this (and to improve my reading habits) this post takes a different approach to the typical reading list blog post…

What follows is a list of books that I aim to read in 2019. The condition for a book to make this list is that it has to have been on my bookshelf for more than one year. Along with each book on this list, there is a bit of history as to why I was drawn to it in the first place. And in some cases, notes as to why an earlier reading attempt failed.

The list:

Pattern Recognition and Machine Learning

Christopher Bishop

This is a book I bought early on in my foray into Machine Learning. After completing Andrew Ng’s ml-class (which later became one of the first classes in the Coursera portfolio), I was looking for a good follow-up text. PRML was highly praised in a lot of discussions I found online, and covered a lot of the same topics in much more detail.

When it arrived, I made a reasonable effort to read it, but found that my math background was not strong enough to digest the content. This was actually quite disappointing at the time. It wasn’t that I couldn’t learn the concepts, it was that I did not yet know where to go to find the answers I was looking for.

Several years later, I feel that this book is very worthy of another attempt. Even flipping through the book today, it is obviously a very rigorous treatment of the fundamentals of Machine Learning, and avoids a lot of the hand-wavey deep learning material that dominates the field at the moment.

Even with a bit more math behind me, I expect this will still be a challenging read - in part because I fully intend to do the exercises. I hope to report at the end of the year that it was a successful and rewarding endeavour.

For the benefit of other Machine Learning enthusiasts, it’s worth mentioning that this book is now freely available online!

Creativity, Inc.

Amy Wallace and Ed Catmull

I first noticed Creativity Inc. while attending SIGGRAPH in 2014. I have long been a fan of Pixar’s earlier movies, and as recently as a few years ago, I considered pursuing a career in 3D rendering technology, so this immediately jumped out at me as something that I would like to read. However, at that point, I had already bought a few books and decided that this one could wait.

It was a couple of years later that I found a copy of Creativity Inc. while browsing a local bookstore. I bought the book, but have consistently deferred reading it, mostly because I know it will be an easy read (when picking something to read, I usually have an appetite for something more challenging).

From what I know of the history of Pixar, I expect this will be an interesting read, especially given that much of what lead to their success was so incredibly unlikely (though that shouldn’t come as a surprise to anyone that knows about Steve Jobs’ role in all of this).

Although working in the 3D animation industry is no longer something that appeals to me, I’m hoping that this book will be a source of inspiration, none-the-less.

Darwin among the Machines

George Dyson

When I found this book at a second-hand bookstore, I decided to buy it mostly out of curiosity, and encouraged by seeing the name of the author.

Generally, I find books that cover the history of computing technology to be repetitive, as there does not seem to be a whole lot in dispute about how it all happened (I could be wrong about that). But when an author with the pedigree of George Dyson writes about the essence of your field, it’s worth taking notice.

After rediscovering it on my bookshelf a few days ago, I was disappointed that I had so easily forgotten to read it. Even if this book offered just one insight about where technology is headed, based on where we’ve come from, it will be well worth the effort.

That’s it?

I’ve intentionally kept this list very short, because I want it to be achieveable, while allowing me to pick up plenty of unexpected reading along the way. All-in-all, this is the first (small) step in reducing the number of unread titles on my bookshelf.