/nlp-in-practice

Full working examples in Python with accompanying dataset for Text Mining & NLP. Includes: Gensim Word2Vec, phrase embeddings, keyword extraction with TFIDF, word count with pyspark, simple text preprocessing, accessing pre-trained embeddings and more.

Primary LanguageJupyter Notebook

NLP-IN-PRACTICE

Use these NLP, Text Mining and Machine Learning code samples and tools to solve real world text data problems.

Notebooks / Source

Links in the first column take you to the subfolder/repository with the source code.

Task Related Article Source Type Repository
Large Scale Phrase Extraction phrase2vec article python script kavgan/phrase-at-scale
Word Cloud for Jupyter Notebook and Python Web Apps word_cloud article python script + notebook kavgan/word_cloud
Gensim Word2Vec (with dataset) word2vec article notebook kavgan/nlp-in-practice
Reading files and word count with Spark spark article python script kavgan/nlp-in-practice
Extracting Keywords with TF-IDF and SKLearn (with dataset) tfidf article notebook kavgan/nlp-in-practice
Text Preprocessing text preprocessing article notebook kavgan/nlp-in-practice
TFIDFTransformer vs. TFIDFVectorizer tfidftransformer and tfidfvectorizer usage article notebook kavgan/nlp-in-practice
Accessing Pre-trained Word Embeddings with Gensim Pre-trained word embeddings article notebook kavgan/nlp-in-practice

Resources

Contact

This repository is maintained by Kavita Ganesan. Please contact me directly if you have questions.