Tag

#Machine Learning

Machine learning is the broader discipline that contains the current AI moment, and these posts pull back to the foundations the hype tends to skip. I write about the actual techniques, supervised and unsupervised learning, the bias-variance tradeoff, the evaluation metrics that matter and the ones that mislead, and the engineering discipline required to ship a model that does not degrade the week after launch. The pieces here are for people who want to understand the field without enrolling in a degree program, covering the intuitions behind the math and the practical wisdom that textbooks often omit. Machine learning is not magic and it is not a fad. It is a set of tools with known limits, and respecting those limits is what makes the tools useful.