Deep Learning for Natural Language Processing - Word Vectors

In this course you will learn to solve a wide range of applied problems in Natural Language Processing, such as text representation, information extraction, text mining, word sense disambiguation, language modeling, similarity detection, and text summarization. The approaches studied in this course focus on neural network architectures such as recurrent neural networks, sequence-to-sequence, and transformers.

0:00 Outline
0:38 Lexical Semantics
31:35 Word Embeddings
43:41 Word2vec
1:19:28 Global Vectors GloVe
1:37:54 NLP Tasks and Evaluation

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