Blaze is a state-of-the-art fire detection and analysis machine learning model. Using the heat of sentiment analysis, it's more than just a flash in the pan – it's a roaring blaze that revolutionizes the way we understand and respond to fire.
Blaze brings unprecedented accuracy in its predictions:
- Temperature Analysis: Achieving an impressive
98.90%accuracy with LSTM, Blaze is an expert in temperature-based fire predictions. 🌡️ - NLP Analysis: With a scorching
99.77%accuracy using BERT for text classification, Blaze has mastered the art of fire-related content detection in social media. 🐦
- Blazingly Fast: With a fiery algorithm that's hotter than a chili pepper, Blaze cuts through the noise and delivers results in a flash.:rocket:
- BERT for Text Classification: By leveraging the BERT model, Blaze sparks insight into message information from social media, like Twitter, to detect and classify fire-related content. 🐦
- LSTM for Temperature Analysis: With an LSTM that's as hot as a summer's day, Blaze can predict when a fire is occurring or about to occur through temperature analysis. 🌡️
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Clone the repository
git clone https://github.com/BlazeWatch/blaze.git
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Install the requirements
cd blaze pip install -r requirements.txt -
Rename
EXAMPLE.envto.envand populate with your data
Get your models fired up by running:
python train-bert.pyto train BERT, and run machine-learning.ipynb to train the rest.
Think you can fan the flames of innovation? Fork the project, create a feature branch, and send us a pull request!
Blaze is available under the MIT License. See LICENSE for more information.
Set your projects on fire with Blaze, where technology and innovation are hotter than ever! 🔥 Feel the heat and join the revolution today!