https://github.com/falcowinkler/nlp-getting-started

study group code for the kaggle challenge
https://github.com/falcowinkler/nlp-getting-started

Last synced: about 2 months ago
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study group code for the kaggle challenge

• Host: GitHub
• URL: https://github.com/falcowinkler/nlp-getting-started
• Owner: falcowinkler
• Created: 2020-06-11T08:44:58.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2023-02-16T01:41:11.000Z (almost 2 years ago)
• Last Synced: 2023-03-10T20:12:12.650Z (almost 2 years ago)
• Language: Python
• Size: 211 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 7
• Metadata Files:
  • Readme: README.md

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README

        
Binary tweet classification

This was an experiment to use word vectors for a simple classification task.

Idea:

- Map every word to it's corresponding word vector (we use globe embeddings)

- Feed the embeddings into a bidirectional LSTM

- Compute output by concatenating the architecture with a dense layer

Validation score on kaggle is around .7 ~ .78

Credits for the hyperparameters go to https://www.kaggle.com/shahules/basic-eda-cleaning-and-glove

Credits for the code to load glove embeddings: https://github.com/ciwin/Intent_Classification

### Run

```bash

export KAGGLE_USERNAME=

export KAGGLE_KEY=

python main.py

```