Build a Natural Language Generation (NLG) System using PyTorch
Overview
- Introduction to Natural Language Generation (NLG) and related things-
- Data Preparation
- Training Neural Language Models
- Build a Natural Language Generation System using PyTorch
Introduction
In the last few years, Natural language processing (NLP) has seen quite a significant growth thanks to advancements in deep learning algorithms and the availability of sufficient computational power. However, feed-forward neural networks are not considered optimal for modeling a language or text. This is because the feed-forward network does not take into consideration the word order in the text.
Hence, to capture the sequential information present in the text, recurrent neural networks are used in NLP. In this article, we will see how we can use a recurrent neural network (LSTM), using PyTorch for Natural Language Generation.
If you need a quick refresher on PyTorch then you can go through the article below:
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