Venture into the world of text vectorization with a focus on TF-IDF (Term Frequency-Inverse Document Frequency) in Python. Through this course, you'll learn how to convert text into numerical features that machine learning models can work with. Using the SMS Spam Collection dataset, you will understand how to apply TF-IDF to prepare text data for predictive modeling.
Overview
Syllabus
- Lesson 1: Transforming Text into Insights: An Introduction to TF-IDF Vectorization in Python
- Lesson 2: Navigating the Weights of Words: Analyzing TF-IDF Scores in NLP
- Lesson 3: Customizing TF-IDF Vectorization Parameters in NLP
- Lesson 4: Optimizing TF-IDF Vectorization by Eliminating Stop Words
