Machine Learning, Data Science, NLP, Dimensionality Reduction, Pca.
general statement, this is just what I found out with my particular data. And especially with PCA, when it is applied to numerical features, I saw it successfully reduce the dimension of the data from 100 or more features to around 10 features while being able to explain 90% of the data variance.