Natural Language Processing with Deep Learning in Python

Complete guide on deriving and implementing word2vec, GLoVe, word embeddings, and sentiment analysis with recursive nets.

Complete guide on deriving and implementing word2vec, GLoVe, word embeddings, and sentiment analysis with recursive nets.

What Will I Learn from the course "Natural Language Processing with Deep Learning in Python"?

• 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

Includes:

• 5 hours on-demand video
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

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