week 11(21-25 october)

After completing my news article recommender last week the upcoming week brought me opportunity to explore a library for high dimensional space visualization t-SNE, I was told by my mentor Mr.Vikram Jha to explore it and tell insights.


t-SNE

t-Distributed Stochastic Neighbor Embedding (t-SNE) is a (prize-winning) technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets.

Before jumping to t-SNE i knew about old technique of dimensionality reduction that is PCA, Principal Component Analysis, I first studied in ISB videos but when Sarabjot sir explained,it  became thorough

PCA

Principal component analysis (PCA) is a technique used to emphasize variation and bring out strong patterns in a dataset. It's often used to make data easy to explore and visualize.

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