---
tags: nlp
---

# 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.

```{gallery-grid}
---
grid-columns: 1
---
- header: "{fas}`book` Count Vectorization and TF-IDF"
  content: "Explore feature extraction with two popular algorithms."
  link: "./textual-feature-extraction-using.html"

- header: "{fas}`book` Creating a Search Engine for your own data using Whoosh"
  content: "Use the `Whoosh` package to create custom search engine for your own data."
  link: "./whoosh-search-engine.html"

- header: "{fas}`book` Traditional Topic Modeling in SKLearn"
  content: "Apply the same principles of TF-IDF to the problem of topic modeling, reorganizing a large corpora into subtopics found in that corpora."
  link: "./traditional-topic-modeling-using.html"

```