Register here: https://bit.ly/3bqNi7T
NLP, also known as computational linguistics, is the combination of AI and linguistics that allows us to talk to machines as if they were human. This session is about an important concept used in the current state of the art applications in Speech Recognition and Natural Language Processing – viz Sequence to Sequence modelling. This will convert an input sequence into an output sequence. Just to give you a sneak peek of the potential application of seq2seq model can be speech recognition, machine translation, question answering, Neural Machine Translation (NMT), and image caption generation.
This workshop will showcase on how to build a language model that we’ll focus on using recurrent neural network which captures the entire context of the input sequence. Seq2seq models typically employ two Recurring Neural Networks (RNNs). The model is trained to map an input sequence to an output sequence which are not necessarily of the same length as each other. The basic structure of the model is a network of encoders and decoder, bidirectional self-attention layer. I will showcase thorough implementation of a content optimization system using NLP techniques along with scalable deployment of model within Cloud.
Register here: https://bit.ly/3bqNi7T
