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Implementation of various Natural Language Processing tasks using PyTorch

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Natural Language Processing using PyTorch

Hype around Deep Learning is centered mostly around Computer Vision, so are gateways to understanding most of the popular frameworks. With the recent advances around Language Technology/ Computational Linguistics or Natural Language Processing as popularly known, getting proper resources to engulf and fully understand the machinations behind it is arduous for starters.

Hence this project is inspired by specialization course of Natural Language Processing by deeplearning.ai offered through Coursera instructed by Younes Bensouda Mourri, Łukasz Kaiser, et.al.

PyTorch has been chosen due to its popularity in academia.

NLP Tasks:

Module Content Status
2 Neural network with GLoVe word embeddings to perform sentiment analysis of Tweets
2 Crosslingual Multi-Aspect sentiment analysis using sentence embeddings
2 Generate synthetic Shakespeare text using a Gated Recurrent Unit (GRU) language model
2 Named Entity Recognition (NER) using LSTMs
2 Siamese LSTM to analyse similar questions
2 Machine Translation using Attention

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