👷♂️ A simple package for extracting useful features from character objects 👷♀️
$ git clone https://github.com/mkearney/textfeatures.gitStarter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.
An experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.
Deep neural network framework for multi-label text classification
dna2vec: Consistent vector representations of variable-length k-mers
Text preprocessing, representation and visualization from zero to hero.
Fast vectorization, topic modeling, distances and GloVe word embeddings in R.
Data from GitHub · snapshot Sep 24, 2026