Introduction to Machine Learning for Time-Series

In previous chapters, we've talked about time-series, time-series analysis, and preprocessing. In this chapter, we'll talk about machine learning for time-series. Machine learning is the study of algorithms that improve through experience. These algorithms or models can make systematic, repeatable, validated decisions based on data. This chapter is meant to give an introduction given both the context and the technical background to much of what we'll use in the remainder of this book.

We'll go through different kinds of problems and applications of machine learning in time-series, and types of analyses relevant to machine learning and time-series analysis. We'll explain the main machine learning problems with time-series, such as forecasting, classification, regression, segmentation, and anomaly detection. We'll then review the basics of machine learning as relevant to time-series. Then, we&apos...