Exploring Dimensionality Reduction on a Small Dataset
What will you learn? In this comprehensive guide, you will delve into the world of dimensionality reduction techniques by exploring how to apply them to a small dataset with dimensions 50×20. You will grasp the fundamentals of Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) through practical implementation. By the end, you’ll have … Read more