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Sequence Models (WEEK 3 (Various sequence to sequence architectures (Basic…
Sequence Models
WEEK 3
Various sequence to sequence architectures
Basic Models
Picking the most likely sentence
Beam Search
Refinements to Beam Search
Error analysis in beam search
BLEU Score
Attention Model Intuition
Attention Model
Speech recognition - Audio data
Speech recognition
Trigger Word Detection
WEEK 1
Recurrent Neural Networks
Why sequence models
Notation
Recurrent Neural Network Model
Backpropagation through time
Different types of RNNs
Language model and sequence generation
Sampling novel sequences
Vanishing gradients with RNNs
Gated Recurrent Unit (GRU)
Long Short Term Memory (LSTM)
Bidirectional RNN
Deep RNNs
Back propagation with RNNs
WEEK 2
Natural Language Processing & Word Embeddings
Natural Language Processing & Word Embeddings
Word Representation
Using word embeddings
Properties of word embeddings
Embedding matrix
Learning Word Embeddings: Word2vec & GloVe
Learning word embeddings
Word2Vec
Negative Sampling
GloVe word vectors
Applications using Word Embeddings
Sentiment Classification
Debiasing word embeddings