Time Series Analysis with Python Cookbook | 10. Building Univariate TSM Using Statistical Methods

Time Series Analysis with Python Cookbook is available from: Packt.com https://bit.ly/3xCNTzQ Amazon: https://amzn.to/3NShZoE This is the “Code in Action” video for chapter 10 of Time Series Analysis with Python Cookbook by Tarek A. Atwan, published by Packt. It includes the following topics: 0:43 Plotting ACF and PACF 1:05 Forecasting univariate time series data with exponential smoothing 2:09 Forecasting univariate time series data with non-seasonal ARIMA 03:15 Forecasting univariate time series data with seasonal ARIMA This book will show you how to implement practical Python solutions for time series analysis and anomaly detection. As you progress, you’ll be able to extract insights and forecast using statistical, machine learning, and deep learning models. Connect with Packt: Find us on Facebook: http://www.facebook.com/PacktPub Find us on Twitter: http://www.twitter.com/packtpub Video created by Tarek A. Atwan