Following my first post on books between the first quadrimester (Jan-Apr), here’s the list for May-Aug. There’s also a post on the books I read read during 2014.
I didn’t read as much as I wanted… but being able to measure how much I’m reading is nice, and I’m coming up with ways to improve on that, e.g. don’t read a book on Haskell and a treatise on Memory written by a historian in parallel.
(I’ve recently discovered that quadrimester is sometimes used as a synonym for quarter in english. Well. In 2016 I might try breaking it into Q1, Q2, Q3, and Q4.)
- The Art of Memory. Frances Yates. (Amazon)
- To Engineer Is Human: The Role of Failure in Successful Design. Henry Petroski. (Amazon)
- The Peripheral. William Gibson. (Amazon)
- Starcraft II: Heaven’s Devils (pt-BR: Demônios do Paraíso). William C. Dietz. (Amazon, Livraria Cultura)
- StarCraft II: Flashpoint (pt-BR: Ponto Crítico). Christie Golden. (Amazon, Livraria Cultura)
- Real World Haskell. Bryan O’Sullivan, Don Stewart, John Goerzen. (book’s site)
- Data Science for Business: What you need to know about data mining and data-analytic thinking. Foster Provost, Tom Fawcett. (Amazon)
That was interesting. I didn’t read everything in The Art of Memory, though. It’s a massive book on how mnemotechnics evolved since the greeks, with an emphasis on what the author calls the Memory Theaters, systems based on astrology, kaballah, and other forms of mysticism, designed to enable its user to remember things. I found parts of the subject fascinating, but the treatment felt a bit verbose at times and I skimmed some sections.
I decided to enjoy some fiction for my own good. Reading about StarCraft made me remember about Rising Lands, and William Gibson’s style is entertaining. Real World Haskell was wonderful (but really hard to go through while practicing it) and book #7 was sort of a “reference” book—I’ve read it in the past, but some of its explanations are useful to introduce non-technical folks to applied Machine Learning, something I tried to do on my last job.
I also wrote a post with my favorite parts of To Engineer Is Human.
- Building LinkedIn’s Real-time Activity Data Pipeline. Ken Goodhope et al. (pdf)
- Investigating app store ranking algorithms using a simulation of mobile app ecosystems. Soo Ling Lim, Peter J. Bentley. 2013 IEEE Congress on Evolutionary Computation (CEC). (IEEE Xplore) Apparently the authors are selling their services based on the simulation environment.
- Representation Learning: A Review and New Perspectives. Yoshua Bengio, Aaron Courville, Pascal Vincent. (arXiv, IEEE Xplore)
I also read a very good blog post related to #1 above—The Log: What every engineer should know about real-time data’s unifying abstraction.
- Assassination Classroom. (only read volume 1)
I didn’t like the story at all. Meh. :(
There will be a list for Sept-Dec in January/2016.