Sequence to Sequence Learning with Encoder-Decoder Neural Network Models by Dr. Ananth Sankar
Channel: ConfEngine
Date: 24/08/2019

In recent years, there has been a lot of research in the area of sequence to sequence learning with neural network models. These models are widely used for applications such as language modeling, translation, part of speech tagging, and automatic speech recognition. In this talk, we will give an overview of sequence to sequence learning, starting with a description of recurrent neural networks (RNNs) for language modeling. We will then explain some of the drawbacks of RNNs, such as their inability to handle input and output sequences of different lengths, and describe how encoder-decoder networks, and attention mechanisms solve these problems. We will close with some real-world examples, including how encoder-decoder networks are used at LinkedIn.

More details: https://confengine.com/odsc-india-2019/proposal/10176

Conference Link: https://india.odsc.com