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LSTM Neural Network for Textual Ngrams

EasyChair Preprint no. 623

6 pagesDate: November 10, 2018


Cognitive neuroscience is the study of how the human brain functions on tasks like decision making, language, perception and reasoning. Deep learning is a class of machine learning problems that use neural networks. They are designed to model the responses of neurons in the human brain. Learning can be supervised or unsupervised. Ngram token models are used extensively in language prediction. Ngrams are probabilistic models that are used in predicting the next word or token. They are a statistical model of word sequences or tokens and are called Language Models or Lms. Ngrams are essential in creating language prediction models. We are exploring a broader sandbox ecosystems enabling for AI. Specifically, around Deep learning applications on unstructured content form on the web.

Keyphrases: cognitive, deep learning, LSTM, neural network, ngrams

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Shaun D'Souza},
  title = {LSTM Neural Network for Textual Ngrams},
  howpublished = {EasyChair Preprint no. 623},

  year = {EasyChair, 2018}}
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