Tutorials about NLP with Python: a bunch of Jupyter notebooks in which I try to teach myself the basics of scikit-learn, nltk, gensim, spacy, keras and pytorch.
Basics:
Text analysis and NLP with Spacy and NLTK, classification with scikit-learn.
Keras:
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Text classification with Keras: the notebook explores a few deep learning approaches to binary sentiment classification on three datasets of reviews (imdb, yelp, amazon), including loading pre-trained glove word embeddings
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Sentiment classification with Keras: the notebook, based on official Keras examples, explores several deep learning approaches to binary sentiment classification on the imdb dataset.
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FastText with Keras: the notebook follows up on the previous one, exploring imdb sentiment classification on top of fastText feature engineering.
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Neural Language modeling with Keras: the notebook contains a few toy examples of neural language modeling in Keras.
PyTorch:
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Introduction to PyTorch
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Classification of names with RNNs
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Name generation with RNNs
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Neural machine translation with attention