hcho3

I switched to Kitty as it was one of the few terminal emulators that supported font ligatures. So far I'm quite satisfied. It's smooth and fast.

+1. I feel the same way. If one out of 20 drive-by contributors stick around and become regular, that would be a real win for me. (I'm currently maintaining a project with 20k GitHub stars and we have four regular contributors.)

Same here in US west

Given that many data people run across is tabular, I appreciate your advice about the importance of statistics. Also kudos for mentioning hypothesis testing (no one in this thread mentioned it). Lastly, I’d add that ML practitioners will gain a lot by listening to statisticians and economists on the issue of data quality, e.g. selection bias.

That said, I am not as cynical about “machine learning.” ML and “data science” brought the importance of prediction front and center, i.e. can you fit a model that accurately predict the target value given a previously seen input? This point is made by the recently published stats textbook Computer Age Statistical Inference (Efron and Hastie).

In some applications, it may be beneficial to choose black box models with high predictive accuracy, as the goal for these applications is prediction, not interpreting individual model coefficients.

Many business data is tabular (possibly with time component), and if you are working with tabular data, the OP’s advice is sound.

I manage a continuous integration server for an open source project that contains CUDA code. To test, we need to run workers with NVIDIA GPUs, and so far I haven't seen a viable alternative to Jenkins.

> “millions of individual adherents“

Is Crossfit a cult? At first I thought the article was a parody or something