Difference between revisions of "Natural Language Processing (NLP)"
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* [http://app.pluralsight.com/library/courses/code-school-breaking-the-ice-with-regular-expressions/table-of-contents Breaking the Ice with Regular Expressions | Code Schol] | * [http://app.pluralsight.com/library/courses/code-school-breaking-the-ice-with-regular-expressions/table-of-contents Breaking the Ice with Regular Expressions | Code Schol] | ||
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<youtube>VrT3TRDDE4M</youtube> | <youtube>VrT3TRDDE4M</youtube> | ||
Revision as of 03:19, 22 September 2018
- Natural Language Processing | Wikipedia
- Grammar Induction | Wikipedia
- Natural Language Tools
- Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Recurrent Neural Network (RNN)
- Global Vectors for Word Representation (GloVe)
- Word2Vec
- Doc2Vec
- Bag-of-Words (scikit-learn: Count Vectorizer)
- Latent Dirichlet Allocation (LDA)
- Autoencoders / Encoder-Decoders
- AI-Powered Search
- Neural Coreference
- Deep Q Learning (DQN)
- NLP News | Sebastian Ruder
- 7 types of Artificial Neural Networks for Natural Language Processing
- Combination of Convolutional and Recurrent Neural Network for Sentiment Analysis of Short Texts | Xingyou Wang, Weijie Jiang, Zhiyong Luo
- Language services | Cognitive Services | Microsoft Azure
- Text Transfer Learning
Speech recognition, speech translation, understanding complete sentences, understanding synonyms of matching words, sentiment analysis, and writing complete grammatically correct sentences and paragraphs.
Regular Expressions (Regex)
Search for text patterns, validate emails and URLs, capture information, and use patterns to save development time.
