In this chapter, we're going to take a brief look at forecasting using regression algorithms. We'll additionally discuss time-series analysis and how we can use techniques from digital-signal processing to aid in our analysis. By the end of the chapter, you will have seen a number of patterns commonly found in time-series and continuous-valued data and will have an understanding of which types of regressions fit on which types of data. Additionally, you will have learned a few digital signal processing techniques, such as filtering, seasonality analysis, and Fourier transformations.
Forecasting is a very broad concept that covers many types of tasks. This chapter will provide you with an initial toolbox of concepts and algorithms that apply broadly to time-series data. We will focus on the fundamentals, and discuss the following...