GitHub - KhaledTofailieh/Corona-Virus-Sentiment-Analysis: In this Notebook I've build some machine-learning and deep-learning to classify corona virus tweets, in both multi class classification and binary classification.

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In this Notebook I've build some machine-learning and deep-learning to classify corona virus tweets, in both multi class classification and binary classification.

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Corona Virus Tweets Multi Class Classification.ipynb		Corona Virus Tweets Multi Class Classification.ipynb
CoronaVirus Tweets Preprocessing.ipynb		CoronaVirus Tweets Preprocessing.ipynb
README.md		README.md

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Hello, This Notebook Contains Example of Corona Virus Tweets Multi Class Classification.

- Classes is: Extremely Positive, Positive, Extremely Negative, Negative.

- We do tweets cleaning, tokenization, normalization, also get the binary classes.

- Try to generate tweets from data.

- Vectorizing texts usiing different vectorization way: BOW, TF-IDF and finally Word Embedding.

- Train different Models(Classifiers) from Scikit-Learn library such as: SVM, Logistic Regression and MulinomialNB for classification.

- Train Deep Neural Networks Models with Tensorflow and Keras such as: LSTM, BiLSTM, CNN and FC for both multi class classification and binary classification.

- Finally we compare results and save the best Model.

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In this Notebook I've build some machine-learning and deep-learning to classify corona virus tweets, in both multi class classification and binary classification.

python nlp machine-learning deep-learning svm scikit-learn cnn lstm tf-idf

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