Dimensionality reduction techniques like PCA, SVD, tSNE, UMAP are fantastic toolset to perform exploratory data analysis and unsupervised learning with high dimensional data. It has become really easy to use many available dimensionality reduction techniques in both R and Python while doing data science. However, often it can be little bit challenging to interpret low… Continue reading 10 quick tips for effective dimensionality reduction