Extracting knowledge from large datasets with large number of variables is always tricky. Dimensionality reduction helps in analyzing high dimensional data, still maintaining most of the information hidden behind complexity. Here are some methods that you must try before further analysis (Part 1).
Before you go
If you enjoyed this post, you will love the newsletter of Data Science at Home. It’s my FREE digest of the best content in Artificial Intelligence, data science, predictive analytics and computer science. Subscribe!