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Become familiar with sequence models

Build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs

Apply RNNs to Character-level Language Modeling

Gain experience with natural language processing, word embeddings, huggingFace tokenizers and transformer models

Learn & implement these for exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), NER, Question Answering and more.