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Build text classification models ( CBOW and Skip-gram) with FastText in python


FastText has been open-sourced by Facebook in 2016 and with its release, it became the fastest and most accurate library in Python for text classification and word representation. It is to be seen as a substitute for gensim package's word2vec. It includes the implementation of two extremely important methodologies in NLP i.e Continuous Bag of Words and Skip-gram model. Fasttext performs exceptionally well with supervised as well as unsupervised learning.

The tutorial will be divided in following four segments :

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