Part 2 – Machine Learning for Time Series

In this part, we will be looking at ways of applying modern machine learning techniques for time series forecasting. This part also covers powerful forecast combination methods and the exciting new paradigm of global models. By the end of this part, you will be able to set up a modeling pipeline using modern machine learning techniques for time series forecasting.

This part comprises the following chapters:

• Chapter 5, Time Series Forecasting as Regression
• Chapter 6, Feature Engineering for Time Series Forecasting
• Chapter 7, Target Transformations for Time Series Forecasting
• Chapter 8, Forecasting Time Series with Machine Learning Models
• Chapter 9, Ensembling and Stacking
• Chapter 10, Global Forecasting Models