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]
