Technical requirements
You will need to set up the Anaconda
environment following the instructions in the Preface of the book to get a working environment with all the libraries and datasets required for the code in this book. Any additional libraries will be installed while running the notebooks.
You need to run the following notebooks for this chapter:
02-Preprocessing_London_Smart_Meter_Dataset.ipynb
inChapter02
01-Setting_up_Experiment_Harness.ipynb
inChapter04
01-Feature_Engineering.ipynb
inChapter06
00-Single_Step_Backtesting_Baselines.ipynb
,01-Forecasting_with_ML.ipynb
, and02-Forecasting_with_Target_Transformation.ipynb
inChapter08
01-Global_Forecasting_Models-ML.ipynb
inChapter10
The associated code for the chapter can be found at https://github.com/PacktPublishing/Modern-Time-Series-Forecasting-with-Python-/tree/main/notebooks/Chapter13.