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Keras 1. Preprocessing from tensorflow.keras.preprocessing.text import Tokenizer t=Tokenizer() fit_text='The earth is an awesome place live' t.fit_on_texts([fit_text]) test_text='The earth is an great place live' sequences=t.texts_to_sequences([test_text])[0] sequences >>>[1, 2, 3, 4, 6, 7] t.word_index >>>{'an': 4, 'awesome': 5, 'earth': 2, 'is': 3, 'live': 7, 'place': 6, 'the': 1} Tokenizer.fi..

word_index Grand index to each words. print(tokenizer.word_index) >>> {'barber': 1, 'secret': 2, 'huge': 3, 'kept': 4, 'person': 5, 'word': 6, 'keeping': 7, 'good': 8, 'knew': 9, 'driving': 10, 'crazy': 11, 'went': 12, 'mountain': 13} word_counts Count the each words. print(tokenizer.word_counts) >>> OrderedDict([('barber', 8), ('person', 3), ('good', 1), ('huge', 5), ('knew', 1), ('secret', 6),..

Corpus Natural Language Data NLP - Natural Language Processing gensim - It is an open source library for unsupervised topic modeling and natural language processing, using modern statistical machine learning. Scikit-learn - SciPy Toolkit. It features various classification, regression and clustering algorithms including support vector machines. NLTK - The Natural Language ToolKit, is a suite of ..