As I work on practicing and solving machine learning (ML) problems, I find myself repeating a set of steps and activities repeatedly.
Thanks to Dr. Jason Brownlee’s suggestions on creating a machine learning template, I have pulled together a project template that can be used to support time series analysis using the ARIMA modeling and Python.
Version 5 of the time series template contains minor adjustments and corrections to the prevision version of the templates. Also, the new template added and updated the sample code to support:
- The new location of the Time Series Data Library datasets (https://dainesanalytics.com/datasets)
- Correcting some predicted time series values that should not be negative. For example, values such as rainfall measurement, disease cases, and stock prices can be zero but cannot be less than zero.
You will find the Python time series template on the Machine Learning Project Templates page.