nlpengine is a collection of Natural Language Processing functions. Its designed to make a NLP engineer's life easier by bundling some of the everyday tasks like data cleaning, feature extraction, text classification, etc. This module is built on top of other popular open source python libraries.
pip install nlpengineThe key featues in the initial release of nlpengine includes:
- Easy to use text classifiers
- Vectorization of texts
- Active Learning (in development)
- Several utility functions
A wrapper on top of Facebook's FastText text classifier to build a text classifier with just few lines of codes.
texts = ["sample sentence one", "just another sentence!", "is this a sentence?"]
labels = ["not question", "not question", "question"]
from nlpengine.classifiers import FastTextClassifier
clf = FastTextClassifier()
model = clf.fit(texts, labels)This module helps convert a corpus of texts to a vector matrix easily. This extracted matrix could be used for further downstream tasks such as text similiarity, vector decomposition & visualization, etc.
from nlpengine.feature_extraction import get_glove_embeddings_from_sentences
texts = ["a great sentence", "and a meaningful one"]
vectors = get_glove_embeddings_from_sentences(texts, download_model=True)