Machine learning is rarely the fundamental enabler of a product, but rather, it often serves as an enhancer.
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!"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!