Each Notebook contains the implementation of a particular model as signified by the file name.
The below notebooks may contain some additional codes for set-up and installation of few libraries as they were run in colab.
- By_article_transfomer.ipynb
- LSTM_GRU.ipynb
- LSTM_GRU_bias.ipynb
Brief description of each Notebook :
- BERT(PyTorch).ipynb : BERT (bert-base-uncased) model trained on by Publisher dataset for 2 epoch.
- By_article_transfomer.ipynb : Experimented on various transformer models on by Article Dataset.
- CNN with batch normalization.ipynb : CNN model with Glove embeddings and batch normaliation on by publisher dataset.
- CNN_Doc2Vec.ipynb : CNN model with Doc2Vec transformation on the by publisher dataset.
- Data Extraction.ipynb : Data extraction into json format from xml datsset using cElementTree.
- DatasetCreation.ipynb : Data extraction from xml datsset using xml.sax.
- Fake_news_cnn_glove.ipynb : CNN model with Glove embeddings and early stop on by publisher dataset , also some work on Bias detection.
- LSTM_GRU.ipynb : Sentiment RNN model with LSTM and Glove Embedding on by publisher dataset.
- LSTM_GRU_bias.ipynb : Sentiment RNN model with LSTM and Glove Embedding on by publisher dataset for bias detection.
- Universal Sentence Encoders.ipynb : Sequential NN model using Universal Sentence Encoders for by publisher Dataset
- Fake_news_detection_NB.ipynb : Naive Bayes and SGDClassifier on by publisher dataset.