Technical requirements

You will need to set up the Anaconda environment by 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 in Chapter02
• 01-Setting_up_Experiment_Harness.ipynb in Chapter04
• 01-Feature_Engineering.ipynb in Chapter06
• 02-One-Step_RNN.ipynb and 03-Seq2Seq_RNN.ipynb in Chapter13 (for benchmarking)
• 00-Single_Step_Backtesting_Baselines.ipynb and 01-Forecasting_with_ML.ipynb in Chapter08

The associated code for the chapter can be found at https://github.com/PacktPublishing/Modern-Time-Series-Forecasting-with-Python-/tree/main/notebooks/Chapter14.