![Overview of Practical Time Series Forecasting using Python: Forecast AirQuality using algorithms like SARIMAX](/uploads/posts/2021-05/1620818277_cov250mk.jpg)
Автор: Aditya Kaushal
Издательство: Amazon.com Services LLC
Год: 2021
Язык: английский
Формат: pdf, azw3, epub
Размер: 14.6 MB
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. The utilization of NumPy, Pandas, Matplotlib, Seaborn, Time Series Forecasting Algorithms like (SARIMAX) Statistical Components, Tableau and Python will help you to gain practical exposure to implement a full-fledged Flask web application to forecast air quality.