A Practical Approach to Timeseries Forecasting Using Python - Model for Underfitting and Overfitting

The video tutorial guides viewers through developing a sequential model using LSTM and dense layers. It covers setting up the model, compiling it with a loss function and optimizer, fitting it with training and validation data, and plotting the training and validation loss using pyplot. The tutorial emphasizes understanding input shapes, choosing the right optimizer, and monitoring model performance through loss plots.

What new insight or understanding did you gain from this video?