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This lecture covers the training of a binary sentiment classifier using a Recurrent Neural Network (RNN) architecture. The topics include data preprocessing (tokenization, stop word removal, lemmatization), training a word embedding model, and training, testing, and improving an RNN. The instructor guides through the process until the exercise session on October 4th.