t-SNE: See 1000-Dimensional Data on a Flat Screen (50 Algorithms #22)

t-SNE (t-Distributed Stochastic Neighbor Embedding) is a non-linear dimensionality-reduction

This is algorithm #22 of the 50 Algorithms Every Programmer Should Know series (Clustering & Dimensionality). You will learn:
- The exact problem t-SNE solves and the intuition behind it
- How it works step by step, with animated diagrams
- The real Python code from the book repo, walked line by line
- Where it is used in practice, its strengths, and its limits
WATCH NEXT
▶ Next: Apriori: How Stores Know What You'll Buy Next (50 Algorithms #23)
https://www.youtube.com/watch?v=l3R2ILMZcCY&list=PLE7n_DIQnYRE
◀ Previously: Principal Component Analysis: Squash High-Dimensional Data Without Losing the Signal (#21 of 50)
https://www.youtube.com/watch?v=Y2BW_95edps&list=PLE7n_DIQnYRE
📺 Full playlist (51 videos): https://www.youtube.com/playlist?list=PLE7n_DIQnYRE

Code (GitHub): https://github.com/cloudanum/50Algorithms/blob/main/Chapter06/Unsupervised_Machine_Learning_Algorithms.ipynb
Book (Amazon): https://www.amazon.com/Algorithms-Every-Programmer-Should-Know/dp/1803247762
neurals.ca: https://neurals.ca
X / Twitter: https://x.com/neurals_ca
Playlist (50 Algorithms): https://www.youtube.com/playlist?list=PLE7n_DIQnYRE

Subscribe to @neurals_ca for the whole series.

#Algorithms #tSNE #ComputerScience #Programming #MachineLearning #50Algorithms #Python #Coding #neuralsca

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