Predicting-Tweet-Sentiment-Maching-Learning-and-streamlit

(I prefere using Visual Studio Code ) Open the folder in VS Code Run the first cell in requirement.ipynb
VS Code will demand to install Jupiter and python, install them , after that return to requirement.ipynb and click Run ALL (you should choose your interpreter of python ) TO train and then Predict !

type in terminal :

python ">>>" import nltk

nltk.download('stopwords')

nltk.download('punkt')

download the CSV file ! https://drive.google.com/file/d/1lcLdqyVG6mlJUom5q9BBxBdI3puRChTn/view?usp=sharing

and save it in Predicting-Tweet-Sentiment-Maching-Learning-and-streamlit FOLDER

in the terminal , run:

pip install streamlit

Now , you can run directly web app because the result of training is already saved in saved_steps1.pkl using pickle
and the result of predicting is in results/result_predictions_1000_tweets.csv

in the terminal : go to the repository of the folder and then run the command :

streamlit run app.py

But if you want to train the model before running the web app

Run All cells in SentimentPrediction.ipynb
you will obtain result_predictions_1000_tweets.csv and saved_steps1.pkl

You can also run twitter.py to get tweets using Twitter API you will obtain result1.csv

Anytime RUN : streamlit run app.py and upload any of the CSV files or type your own statement to predict if it is positive or not

Contactez-moi : [email protected]