This repo contains tutorials covering how to do sentiment analysis using PyTorch 1.8 and torchtext 0.9 using Python 3.7.
The first 2 tutorials will cover getting started with the de facto approach to sentiment analysis: recurrent neural networks (RNNs). The third notebook covers the FastText model and the final covers a convolutional neural network (CNN) model.
There are also 2 bonus "appendix" notebooks. The first covers loading your own datasets with torchtext, while the second contains a brief look at the pre-trained word embeddings provided by torchtext.
If you find any mistakes or disagree with any of the explanations, please do not hesitate to submit an issue. I welcome any feedback, positive or negative!
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