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Deep-Learning-Projects

Hotel-Reviews-Classifier

  1. Classified hotel reviews into 2-class classification as positive/negative and deceptive/truthful reviews using 2-layered network using TensorFlow.
  2. Implemented our own gradient descent and even visualize test data by reducing dimensions using TSNE. You can see in tsne_embeds.pdf
  3. Training data used is same as under Naive Bayes Classifier under NLP Project Repository.
  4. Run starter.py with input data as command line argument.
  5. Got 95% accuracy.

RNN-POS-Tagger

  1. Tagged Italian, Japanese and surprise language using sequence to sequence model using TensorFlow.
  2. Used Bidirectional LSTM to get better accuracy.
  3. Got 96% accuracy for Japanese and Italian languages.

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TensorFlow Projects done during Natural Language Processing course for Masters at USC

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