"What do R2, laboratory error analysis, ensemble learning, meta-analysis, and financial portfolio risk all have in common? The answer is that they all depend on a fundamental principle of statistics that is not as widely known as it should be. Once this principle is understood, a lot of stuff starts to make more sense."
Read it!"Real-time machine learning is largely an infrastructure problem. Solving it will require the data science/ML team and the platform team to work together."
Read it!Asking 'What happens before I do my job?' and 'What happens after I do my job?' can help with choosing what to learn next.
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