Today’s experimental episode uses sound to describe some basic ideas from time series.
This episode codes lag, seasonality, trend, noise, heteroskedasticity, decomposition, smoothing, feature engineering, and deep learning.
Kyle is the founder of Data Skeptic, a popular podcast about artificial intelligence, machine learning, and data science. Outside of hosting the show, he runs a boutique consulting group that helps small and medium enterprise companies deploy data driven automated solutions in the cloud.