When I first started to learn about machine learning, specifically supervised learning, I eventually felt comfortable with taking some input $\mathbf{X}$, and determining a function $f(\mathbf{X})$ that best maps $\mathbf{X}$ to some known output value $y$. Separately, I dove a little into time series analysis and thought of this as a completely different paradigm. In time series, we don’t think of things in terms of features or inputs; rather, we have the time series $y$, and $y$ alone, an...
