I recently began experimenting with spaced repetition memory systems. I was inspired to investigate this after reading Michael Nielsen’s writing on the topic (see here and here). I’m somewhat of a Michael Nielsen super-fan (see this post about a lecture he gave at Georgia Tech), so when he describes something like spaced repetition as being a superpower that radically changed his life, I have to listen closely and take heed. If you’re unfamiliar with Nielsen, I would suggest reading his Principles of Effective Research as a starting point.
Here are the tweets that set me off about spaced repetition:
(Read the entire Twitter stream here.)
I immediately downloaded Anki and began loading it up with machine learning and molecular biology questions.
In an effort to solidify my understanding of spaced repetition and get the most out of using Anki, around a year ago, I prepared a handout and gave a talk at a Junto that I frequently attend. I’m sharing that handout here in hopes that someone may find it useful.
(It was also a good excuse to try out the tufte-latex document class.)
Download the 8-page handout here:
The source is available on Github. Note that I tried to replace a lot of the examples with my own, but likely failed to attribute some ideas which were not my own.
One final note for machine learning people: Chris Albon’s famous Machine Learning Flashcards ship with an Anki-compatible set of images. Although it’s generally best to create your own cards, I have enjoyed using these in the app and highly recommend. They’re worth much more than the $12 price.