Practical Time Series Analysis: Prediction with Statistics and Machine Learning
Language: English
Published by O'Reilly Media, 2019
- Softcover
- Used
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Used - Acceptable: All pages and the cover are intact, but shrink wrap, dust covers, or boxed set case may be missing. Pages may include limited notes, highlighting, or minor water damage but the text is readable. Pages may include limited notes and highlighting, but the text cannot be obscured or unreadable. Any access codes or passwords originally included with the book may be expired, used or no longer valid. Image is stock photo and cover art edition may be different than pictured.
Seller Inventory # MERV.1492041653.A
- Title
- Practical Time Series Analysis: Prediction with Statistics and Machine Learning
- Author
- Nielsen, Aileen
- Publisher
- O'Reilly Media
- Publication year
- 2019
- Condition
- acceptable
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1492041653
- ISBN 13
- 9781492041658
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 challenges in 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
"Synopsis" may belong to another edition of this title.
About the Author
In the recent past, Aileen worked at mobile health platform One Drop and on Hillary Clinton's presidential campaign. She is a frequent speaker at machine learning conferences on both technical and sociological subjects. She holds an A.B. from Princeton University and is A.B.D. in Applied Physics at Columbia University.
"About the title" may belong to another edition of this title.
MERS Goodwill
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AbeBooks seller since March 13, 2026
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