Learn the essential techniques for cleansing and processing text in Python. Discover how to convert text to a form that's ready for analytics and predictions.
Overview
Syllabus
Introduction
- The need for text mining skills in data science
- Text mining today
- Document concepts
- Corpus concepts
- Introduction to the NLTK library
- Setting up the environment
- Reading raw files
- Reading files with corpus reader
- Exploring the corpus
- Analyzing the corpus
- Tokenization
- Cleansing text
- Stop word removal
- Stemming
- Lemmatization
- Building n-grams
- Tagging parts of speech
- Term frequency-inverse document frequency (TF-IDF)
- Building a TF-IDF matrix
- Storing text
- Processing text data
- Scalable processing of text data
- Next steps
Taught by
Kumaran Ponnambalam
