Technical requirements

You will need to set up an Anaconda environment, following the instructions in the Preface of the book, to get a working environment with all the packages and datasets required for the code in this book.

The associated code for the chapter can be found at https://github.com/PacktPublishing/Modern-Time-Series-Forecasting-with-Python-/tree/main/notebooks/Chapter10.

You need to run the following notebooks for this chapter:

• 02-Preprocessing London Smart Meter Dataset.ipynb in Chapter02
• 01-Setting up Experiment Harness.ipynb in Chapter04
• From the Chapter06 and Chapter07 folders:
  • 01-Feature Engineering.ipynb
  • 02-Dealing with Non-Stationarity.ipynb
  • 02a-Dealing with Non-Stationarity-Train+Val.ipynb
• From the Chapter08 folder:
  • 00-Single Step Backtesting Baselines.ipynb
  • 01-Forecasting with ML.ipynb
  • 01a-Forecasting with ML for Test Dataset.ipynb
  • 02-Forecasting with Target Transformation.ipynb
  • 02a-Forecasting with Target Transformation(Test).ipynb

...