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From a Dataset of more than 11k Tweets, needs to be cleaned, all the tweets are geolocated on a map, a word cloud is made in order to see the most used words and a model is trained to see the accuracy of the model to predict if a Tweet is a Disaster or not

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JaimeEV/Tweet_Disasters

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Tweet_Disasters

From a Dataset of more than 11k Tweets, needs to be cleaned, all the tweets are geolocated on a map, a word cloud is made in order to see the most used words and a model is trained to see the accuracy to predict if a Tweet is a Disaster or not

(On Mac)

Installation

  • First create your virtual environment with:

python3 -m venv venv

  • Then Activate it with:

source venv/bin/activate

  • To install the requirement.txt files in order to get all the dependencies, you can do that with:

pip install -r requirements.txt

  • run the jupyter notebook to see the files on your browser with:

jupyter notebook

  • Find the file Tweets_Disasters.ipynb and open it.

About

From a Dataset of more than 11k Tweets, needs to be cleaned, all the tweets are geolocated on a map, a word cloud is made in order to see the most used words and a model is trained to see the accuracy of the model to predict if a Tweet is a Disaster or not

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