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Simple streamlit app for road traffic forecasting in Belgium with an LSTM-based encoder-decoder model architecture

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giobbu/App_Traff_Forecast_DeapLearn

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Deap Learning Model for Traffic Forecasting

demo.mp4

Build Image from Dockerfile

To create an image first:

git clone https://github.com/giobbu/App_Traff_Forecast_DeapLearn 
cd App_Traff_Forecast_DeapLearn 

Then run:

docker build -t giobbu/deap_traff_app .

Check the image created:

docker image list

Pull Image from Docker Hub

To downloaded the image from Docker Hub:

docker pull giobbu/deap_traff_app

Run Streamlit App Container

To interact with the App type:

docker run -p 8501:8501 --rm giobbu/deap_traff_app

view your Streamlit app in your browser

localhost:8501

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Simple streamlit app for road traffic forecasting in Belgium with an LSTM-based encoder-decoder model architecture

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