Natural Language Processing with Deep Learning in Python

Natural Language Processing with Deep Learning in Python

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Natural Language Processing with Deep Learning in Python

Natural Language Processing with Deep Learning in Python, Complete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets

Created by Lazy Programmer Inc.

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What you'll learn
  • Understand and implement word2vec
  • Understand the CBOW method in word2vec
  • Understand the skip-gram method in word2vec
  • Understand the negative sampling optimization in word2vec
  • Understand and implement GloVe using gradient descent and alternating least squares
  • Use recurrent neural networks for parts-of-speech tagging
  • Use recurrent neural networks for named entity recognition
  • Understand and implement recursive neural networks for sentiment analysis
  • Understand and implement recursive neural tensor networks for sentiment analysis

Requirements
  • Install Numpy, Matplotlib, Sci-Kit Learn, Theano, and TensorFlow (should be extremely easy by now)
  • Understand backpropagation and gradient descent, be able to derive and code the equations on your own
  • Code a recurrent neural network from basic primitives in Theano (or Tensorflow), especially the scan function
  • Code a feedforward neural network in Theano (or Tensorflow)
  • Helpful to have experience with tree algorithms

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