Class

https://courses.nvidia.com/dashboard

Linguistic Concepts

• conference - anaphors
• gang of four design
• null subject
• recursion

Word Embeddings

• HMMS, CRF, PGMs
  • CBoW -Bag of Words / ngrams - feature per word/n items
  • 1-hot Sparse input - create a vector the size of the entire vocabulary
• Stop Words
• TF-IDF

Word2Vec

Skip-Gram

• Firth 1957 Distributional Hypothess

• Word Cloud

Financial News

Yuval

Tools:

• Glove
  • dot product
• FastText
  • Skipgram
  • Continuous bag of words

Multi-channel LSTM Network Keras wih TensorFlow Utilize the GloVe and FastText Skipgram pretrained embeddings, allows he underlying network to access larger feature space to build complex features on top of.

Can use utilize combinations of various corpus and embedding methods for better performance

Bidirectional LSTM network is used o encode sequential information on the embedding layers.

Dense layer to project fnal output classification

Use embedding... embeddings = transfer learning

? CNN vs BI-LSTM (RNN) this approach, BI-LSTM does not need a lot of data

Attention mechanism -- translate ... you can look back

                   ... not a fixed vector size