Python Natural Language Processing

Exercise

Read about undersampling and oversampling techniques.

Now it's time to understand how we can improvise our model after the first iteration, and sometimes, feature engineering helps us a lot in this. In Chapter 5, Feature Engineering and NLP Algorithms and Chapter 6, Advance Feature Engineering and NLP Algorithms, we explained how to extract features from text data using various NLP concepts and statistical concepts as part of feature engineering. Feature engineering includes feature extraction and feature selection. Now it's time to explore the techniques that are a part of feature selection. Feature extraction and feature selection give us the most important features for our NLP application. Once we have these features set, you ...