A Practical Approach to Timeseries Forecasting Using Python - Dataset Division

The video tutorial explains how to create and manipulate two lists, train X and train Y, for a machine learning model. It covers setting future and past values, defining a range for these lists, and appending values to them. The tutorial also demonstrates converting these lists into arrays and understanding their shapes. Finally, it introduces the implementation of an LSTM model.

What are the two lists that need to be created for training?

Explain the significance of the variables north_future and N_past in the context of the training data.

How do you determine the range for updating train X and train Y?

What is the process for appending values into train X?

Describe how train Y is populated in relation to train X.

What is the purpose of converting train X and train Y into arrays?

What are the shapes of train X and train Y after the data preparation process?