Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Machine Learning for Time-Series with Python

You're reading from   Machine Learning for Time-Series with Python Forecast, predict, and detect anomalies with state-of-the-art machine learning methods

Arrow left icon
Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781801819626
Length 370 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Ben Auffarth Ben Auffarth
Author Profile Icon Ben Auffarth
Ben Auffarth
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Introduction to Time-Series with Python 2. Time-Series Analysis with Python FREE CHAPTER 3. Preprocessing Time-Series 4. Introduction to Machine Learning for Time-Series 5. Forecasting with Moving Averages and Autoregressive Models 6. Unsupervised Methods for Time-Series 7. Machine Learning Models for Time-Series 8. Online Learning for Time-Series 9. Probabilistic Models for Time-Series 10. Deep Learning for Time-Series 11. Reinforcement Learning for Time-Series 12. Multivariate Forecasting 13. Other Books You May Enjoy
14. Index

What Is a Time-Series?

Since this is a book about time-series data, we should start with a clarification of what we are talking about. In this section, we'll introduce time-series and their characteristics, and we'll go through different kinds of problems and types of analyses relevant to machine learning and statistics.

Many disciplines, such as finance, public administration, energy, retail, and healthcare, are dominated by time-series data. Large areas of micro- and macro-economics rely on applied statistics with an emphasis on time-series analyses and modeling. The following are examples of time-series data:

  • Daily closing values of a stock index
  • Number of weekly infections of a disease
  • Weekly series of train accidents
  • Rainfall per day
  • Sensor data such as temperature measurements per hour
  • Population growth per year
  • Quarterly earnings of a company over a number of years

This is only to name but a few. Any data...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime