Spacy’s English large and medium size models are shipped with Glove word embeddings. In this tutorial, we will do news classification (fake vs real) using these word embeddings. We will train the Multinomial Naive Bayes classifier and KNN classifier to train the model and compare their performance.
Code: https://github.com/codebasics/nlp-tutorials/blob/main/14_word_vectors_spacy_text_classification/word_vectors_spacy_text_classification.ipynb
Exercise: https://github.com/codebasics/nlp-tutorials/blob/main/14_word_vectors_spacy_text_classification/spacy_word_embeddings_exercise.ipynb
Complete NLP Playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uuvuAXhYjV2lMEShq2UYSwX
Dataset credit: https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset
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