Difference between revisions of "NLP Keras model in browser with TensorFlow.js"
| Line 31: | Line 31: | ||
*** Word Embedding | *** Word Embedding | ||
** [[Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Recurrent Neural Network (RNN)]] | ** [[Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Recurrent Neural Network (RNN)]] | ||
| − | ** [[Attention Mechanism/ | + | ** [[Attention]] Mechanism/[[Transformer]] Model |
** [[Global Vectors for Word Representation (GloVe)]] | ** [[Global Vectors for Word Representation (GloVe)]] | ||
Revision as of 13:55, 29 June 2019
Youtube search... | ...Google search
How to use your Keras model in browser with tensorflow.js
- NLP Keras model in browser with TensorFlow.js | Mikhail Salnikov - Towards Data Science
- The Unreasonable Effectiveness of Recurrent Neural Networks | Andrej Karpathy - Towards Data Science
- Natural Language Tools & Services:
- Datasets:
- Sequence to Sequence (Seq2Seq) Model:
- Natural Language Processing (NLP):
- Named Entity Recognition (NER)
- Word Embedding
- Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Recurrent Neural Network (RNN)
- Attention Mechanism/Transformer Model
- Global Vectors for Word Representation (GloVe)
- Natural Language Processing (NLP):
SOTA = State of the Art
Mr. [B-PER] Johnson [I-PER] like Moscow! [B-LOC]
