Text Processing

In these notebooks, we explore the traditional techniques for processing and analyzing text. This includes using Term Frequency-Inverse Document Frequency (TF-IDF) for feature extraction, creating a search engine and topic modelling. Just like the introductory notebooks, these skills will be pivotal in future lessons and notebooks.

Count Vectorization and TF-IDF

Explore feature extraction with two popular algorithms.

./textual-feature-extraction-using.html

Creating a Search Engine for your own data using Whoosh

Use the Whoosh package to create custom search engine for your own data.

./whoosh-search-engine.html

Traditional Topic Modeling in SKLearn

Apply the same principles of TF-IDF to the problem of topic modeling, reorganizing a large corpora into subtopics found in that corpora.

./traditional-topic-modeling-using.html