For data science projects I recommend using source control or version control, and committing changes at a very fine level of granularity. This means checking in possibly broken code, and the possibly weak commit messages (so when working in a shared project, you may want a private branch or second […]
I strongly advise using version control, and usually recommend using git as your version control system. Usually I feel a bit guilty about this advice as git is so general that it is more of a toolkit for a version control system than a complete proscriptive version control system (the […]
There is no excuse for a digital creative person to not use some sort of version control or source control. In the past disk space was too dear, version control systems were too expensive and software was not powerful enough; this is no longer the case. Unless your work is […]