24.10 Other techniques

• Read R blogs to see what performance problems other people have struggled with, and how they have made their code faster.

• Read other R programming books, like The Art of R Programming or Patrick Burns’ R Inferno to learn about common traps.

• Take an algorithms and data structure course to learn some well known ways of tackling certain classes of problems. I have heard good things about Princeton’s Algorithms course offered on Coursera.

• Learn how to parallelise your code. Two places to start are Parallel R and Parallel Computing for Data Science

• Read general books about optimisation like Mature optimisation or the Pragmatic Programmer

• Read more R code. StackOverflow, R Mailing List, DSLC, GitHub, etc.