Natural Language Processing with Sequence Models

Por: Coursera . en: , ,

  • Neural Networks for Sentiment Analysis
    • Learn about neural networks for deep learning, then build a sophisticated tweet classifier that places tweets into positive or negative sentiment categories, using a deep neural network.
  • Recurrent Neural Networks for Language Modeling
    • Learn about the limitations of traditional language models and see how RNNs and GRUs use sequential data for text prediction. Then build your own next-word generator using a simple RNN on Shakespeare text data!
  • LSTMs and Named Entity Recognition
    • Learn about how long short-term memory units (LSTMs) solve the vanishing gradient problem, and how Named Entity Recognition systems quickly extract important information from text. Then build your own Named Entity Recognition system using an LSTM and data from Kaggle!
  • Siamese Networks
    • Learn about Siamese networks, a special type of neural network made of two identical networks that are eventually merged together, then build your own Siamese network that identifies question duplicates in a dataset from Quora.

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