Generative Adversarial, Python, Synthetic Data, Gans, Time Series Analysis.
essentially train the TimeGAN model on our energy_data and then use that trained model to generate more. Where the parameters to be fed to TimeGAN constructor have to be defined appropriately according to our requirements. We have n_seq defined as 28 (features), seq_len defined as 24 (timesteps).