Skip to Content
Modern Time Series Forecasting with Python
book

Modern Time Series Forecasting with Python

by Manu Joseph
November 2022
Beginner to intermediate
552 pages
16h 4m
English
Packt Publishing
Content preview from Modern Time Series Forecasting with Python

6

Feature Engineering for Time Series Forecasting

In the previous chapter, we started looking at machine learning (ML) as a tool to solve the problem of time series forecasting. We also talked about a few techniques such as time delay embedding and temporal embedding, which cast time series forecasting problems as classical regression problems from the ML paradigm. In this chapter, we’ll look at those techniques in detail and go through them in a practical sense using the dataset we have been working with throughout this book.

In this chapter, we will cover the following topics:

  • Feature engineering
  • Avoiding data leakage
  • Setting a forecast horizon
  • Time delay embedding
  • Temporal embedding

Technical requirements

You will need to set up the Anaconda ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Modern Time Series Forecasting with Python - Second Edition

Modern Time Series Forecasting with Python - Second Edition

Manu Joseph, Jeffrey Tackes

Publisher Resources

ISBN: 9781803246802Supplemental Content