In this book, we will cover the most common types of ML, but from a probabilistic perspective.
Roughly speaking, this means that we treat all unknown quantities (e.g., predictions about the
future value of some quantity of interest, such as tomorrow’s temperature, or the parameters of some
model) as random variables, that are endowed with probability distributions which describe a
weighted set of possible values the variable may have.Lee mas.
Las técnicas y herramientas cubiertas en Probabilistic Machine Learning: An Introduction son muy similares a los requisitos que se encuentran en los anuncios de trabajo de Científico de datos.
