I’ve been reading some books:
1984 and Starship Troopers
I don’t have a lot of time to read fiction due to work and study, so I started listening to audiobooks during my commute, and whenever I’m driving, in general. I’ve discovered that can get through books surprisingly quickly this way – 1984 and Starship Troopers took me roughly 2 weeks each to finish, both of which are about 300 pages long in print. I started first with Starship Troopers since the title was recognizable – I had seen the film adaptation first, but I found the book much more enjoyable – the movie was mostly an action-packed bloodbath whereas the book focused more on Juan Rico’s development as a soldier living under an authoritarian regime; training as a recruit and then as an officer. In this sense, the plots were almost completely different, and in my opinion the film really butchered the book. For example, the main character’s nationality was Filipino, which was actually an important point as the book was written during a particularly sensitive time with respect to race in the United States. This aspect was completely absent in the film adaptation.
I picked up 1984 so I could understand all the cultural references that I’ve seen in the media. It read like an adult version of Animal Farm, and touched upon many of the same subjects with respect to totalitarianism and the Communist revolution. It even had two characters representing Stalin (Big Brother) and Trotsky (Goldstein), just like animal farm did (Napoleon and Snowball, respectively). I thought the plot was okay, but it was really the ideas on state censorship, surveillance, and historical revisionism that stuck me as important, and these ideas were probably what made the book so culturally important. It was also one of the most quotable books I’ve ever read. I recognized some references that I already knew came from the book, but also some new ones that I didn’t realize were inspired by 1984:
- Big Brother is watching you
- We have always been at war with Eastasia
- Hate Week
- The chocolate rations have been reduced
- Room 101
- Newspeak, Doublethink
- Thoughtcrime
- Thought Police
There were a lot more, but that’s what I could think of off the top of my head. After 1984, I started reading Asimov’s Foundation, which I thought contained some pretty neat ideas on what society would be like in an age where humans have mastered interstellar travel. The book is mostly dialogue, which I found dry after the first few chapters. I’m currently reading this right now although I find that I have to switch between listening to the radio and the audiobook due to the lack of plot.
Modern Database Management
I’m reading Modern Database Management to get a better understanding of database design and structure. Several people have asked me why I’ve spent the time to do so and I’ve responded that it’s to better understand how data are stored in an organization, as well as how IT departments are structured so as to facilitate communication between myself and my coworkers in IT. I also think that learning how to write queries efficiently and effectively in SQL will increase my productivity and facility when it comes to manipulating data. This is often the most time-consuming task when it comes to performing statistical analyses, so I think these gains will be well worth the investment (about 200 hours or so).
Data Mining: Practical Machine Learning Tools and Techniques
I’ve decided to spend a little bit of time each day (30 minutes or so), reading advanced technical material that is beyond reach of my current level of proficiency. This is not so much for understanding but moreso for exposure to new subjects that I might want to study in the near future. I picked up Data Mining because it’s been heavily touted by the media as “the next big thing,” so I wanted to see what it was all about (although we must approach such claims with caution). I actually use some of these techniques at work – such as building regression models and using cross validation. The book is surprisingly accessible, and not very technical. I actually found the first few chapters accessible and enjoyable, and didn’t struggle like I thought I would. It mostly covers the purpose, motivations, and importance of data mining techniques and points the reader to external material should they want to explore the topic further. In my opinion it’s actually important to have a non-technical text on the subject, as many data mining tools are implemented via different computer languages and software packages – for example, it might not benefit the reader (or at least it would inconvenience him) if the book focused on the nuts and bolts of one computer language whereas his employer used another.
For this type of reading I’m not aiming at 100% understanding, I’m mostly reading these to see where I should go next, and to gain familiarity with the vocabulary and terminology used in certain subject areas. Should I ever decide to look into a subject more deeply, I’ll come back to a text for a second reading once I master the subject’s prerequisites.