Practical time series analysis : prediction with statistics and machine learning / Aileen Nielsen.

Format:

Book

Author/Creator:

Nielsen, Aileen, author.

Language:

English

Subjects (All):

Machine learning.

Artificial intelligence.

Physical Description:

1 online resource (xvi, 480 pages) : colour illustrations

Edition:

First edition.

Place of Publication:

Sebastopol, CA : O'Reilly Media, Incorporated, 2019.

System Details:

text file

Summary:

Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance

Contents:

1. Time Series: An Overview and a Quick History

2. Finding and Wrangling Time Series Data

3. Exploratory Data Analysis for Time Series

4. Simulating Time Series Data

5. Storing Temporal Data

6. Statistical Models for Time Series

7. State Space Models for Time Series

8. Generating and Selecting Features for a Time Series

9. Machine Learning for Time Series

10. Deep Learning for Time Series

11. Measuring Error

12. Performance Considerations in Fitting and Serving Time Series Models

13. Healthcare Applications

14. Financial Applications

15. Time Series for Government

16. Time Series Packages

17. Forecasts About Forecasting

Notes:

Includes bibliographical references and index.

Description based on online resource; title from digital title page (viewed on November 11, 2019).

ISBN:

9781492041603

1492041602

9781492041641

1492041645

9781492041627

1492041629

OCLC:

1121139481