Sequence to Sequence Learning with PyTorch

To blast off the year, we are excited to have Liling Tan, data scientist and NLP guru from Rakuten to share with us Sequence to Sequence Learning with PyTorch!

Sequence to Sequence (Seq2Seq) learning is a useful class of neural network model to map sequential input into an output sequence. It has been shown to work well on various task, from machine translation to interpreting Python without an interpreter. This will be a hands-on session to write an encoder-decoder Seq2Seq network using PyTorch

Bio

Liling is a data geek who works mostly with text processing and machine translation. He works as a research scientist at Rakuten Asia. https://www.linkedin.com/in/alvations/

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