https://github.com/adirthaborgohain/lstm-classifier-with-hyperparameter-tuning
A simple bidirectional LSTM Classifier to classify sentiments on a text. Hyperparameter tuning is done using Randomized CV Search to find best parameters for the deep learning model.
https://github.com/adirthaborgohain/lstm-classifier-with-hyperparameter-tuning
keras lstm-neural-networks parameter-tuning rnn sentiment-analysis
Last synced: 2 months ago
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A simple bidirectional LSTM Classifier to classify sentiments on a text. Hyperparameter tuning is done using Randomized CV Search to find best parameters for the deep learning model.
- Host: GitHub
- URL: https://github.com/adirthaborgohain/lstm-classifier-with-hyperparameter-tuning
- Owner: AdirthaBorgohain
- Created: 2021-10-17T12:11:02.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2021-10-17T12:12:43.000Z (over 4 years ago)
- Last Synced: 2025-03-30T11:27:50.698Z (over 1 year ago)
- Topics: keras, lstm-neural-networks, parameter-tuning, rnn, sentiment-analysis
- Language: Jupyter Notebook
- Homepage:
- Size: 9.98 MB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: readme.txt
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README
Before running the notebook, you will need to have the glove embeddings file in the same directory as of the project. You can either download it manually from http://nlp.stanford.edu/data/glove.6B.zip and unzip it int he same directory OR open a terminal and execute the following commands after navigating to the same directory as of the project folder:
1. wget http://nlp.stanford.edu/data/glove.6B.zip
2. unzip glove*.zip
3. rm *.zip glove.6B.50d.txt glove.6B.100d.txt glove.6B.200d.txt