Predictive Analytics with TensorFlow 9.3: Developing a Predictive Model for Time Series Data

This video tutorial focuses on developing a predictive model for time series data using LSTM networks. It begins with an introduction to the application of RNNs, specifically LSTMs, in time series prediction due to temporal dependencies. The tutorial then covers data preparation, including loading and splitting the dataset into training and test sets. The construction and training of the LSTM model are detailed, followed by testing and evaluating its performance. The video concludes with a summary and a preview of the next topic, sentiment analysis using LSTM.

Explain the significance of the 'train' method in the LSTM network.

What is the purpose of the 'plot_results' function in the context of the LSTM model?