An Overview of Practical Time Series Forecasting using Python: Forecast AirQuality using algorithms like SARIMAX Front Cover

An Overview of Practical Time Series Forecasting using Python: Forecast AirQuality using algorithms like SARIMAX

  • Length: 29 pages
  • Edition: 1
  • Publication Date: 2021-05-10
  • ISBN-10: B094P4HBGD
Description

This is a short book to show the readers how to build a Time Series Model using mathematical models, Python and concepts of statistics to predict real-time air quality in a local mapped area by using open source data. The main objective of this book is to teach the readers about forecasting algorithms like SARIMAX and how to build a Python project to forecast and monitor air pollution to track personal exposure to PM 2.5. At the end of the book, you will have a good understanding of SARIMAX Algorithm to make a good forecast Particulate Matter 2.5 (PM 2.5) similar to what Sci-kit – Learn regression algorithms provide.
This book can be a foundation to build a mobile application/web application to forecast air quality.

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