"Sequence classification has a broad range of applications
such as genomic analysis, information retrieval, health informatics, finance, and abnormal detection…."
Ref: Theory:
https://www.cs.sfu.ca/~jpei/publications/Sequence%20Classification.pdf
Sequence Classification in Keras/Python, LSTM, GRU, BIDirectional LSTM
https://machinelearningmastery.com/develop-bidirectional-lstm-sequence-classification-python-keras/
Sequence Classification Using Deep Learning
"This example uses the Japanese Vowels data set as described in [1] and [2]. This example trains an LSTM network to recognize the speaker given time series data representing two Japanese vowels spoken in succession"
Character to Character level Sequence to Sequence Modeling:
https://github.com/keras-team/keras/blob/master/examples/lstm_seq2seq.py
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever, Oriol Vinyals, Quoc V. Le
https://arxiv.org/abs/1409.3215
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://arxiv.org/abs/1406.1078
Dataset:
Tab-delimited Bilingual Sentence Pairs
http://www.manythings.org/anki/
Sayed Ahmed
sayedum
Linkedin: https://ca.linkedin.com/in/sayedjustetc
Blog: http://sitestree.com, http://bangla.salearningschool.com
