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Natural Language Processing with Deep Learning in Python

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Overview

Complete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets What you'll learn: Understand and implement word2vecUnderstand the CBOW method in word2vecUnderstand the skip-gram method in word2vecUnderstand the negative sampling optimization in word2vecUnderstand and implement GloVe using gradient descent and alternating least squaresUse recurrent neural networks for parts-of-speech taggingUse recurrent neural networks for named entity recognitionUnderstand and implement recursive neural networks for sentiment analysisUnderstand and implement recursive neural tensor networks for sentiment analysisUse...

Syllabus

  • Outline, Review, and Logistical Things
  • Beginner's Corner: Working with Word Vectors
  • Review of Language Modeling and Neural Networks
  • Word Embeddings and Word2Vec
  • Word Embeddings using GloVe
  • Unifying Word2Vec and GloVe
  • Using Neural Networks to Solve NLP Problems
  • Recursive Neural Networks (Tree Neural Networks)
  • Theano and Tensorflow Basics Review
  • Appendix / FAQ Finale


Natural Language Processing with Deep Learning in Python
Go to Class

via Udemy

12 hours 2 minutes

Certificate Available

English

On-Demand

Advanced

Instructor

Lazy Programmer Inc.

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