"In real life, we weigh the anticipated consequences of the decisions that we are about to make. That approach is much more rational than limiting the percentage of making the error of one kind in an artificial (null hypothesis) setting or using a measure of evidence for each model as the weight."
Longford (2005) http://www.stat.columbia.edu/~gelman/stuff_for_blog/longford.pdf
Many companies are currently scrambling for ML infra engineers. They need people that know how to manage AI infrastructure, and that can seriously speed up training and inference with specialized tooling like vLLM, Triton, TensorRT, Torchtune, etc.
"Extract Year from a datetime column", by Piyush Raj: https://datascienceparichay.com/article/pandas-extract-year-from-datetime-column/
An easy guide to predict possible future quantities, by Mercy Kibet: https://www.influxdata.com/blog/guide-regression-analysis-time-series-data/#heading0
