t-distributed Stochastic Neighbor Embedding (t-SNE) | Dimensionality Reduction Techniques (4/5) скачать в хорошем качестве

t-distributed Stochastic Neighbor Embedding (t-SNE) | Dimensionality Reduction Techniques (4/5)

To try everything Brilliant has to offer—free—for a full 30 days, visit https://brilliant.org/DeepFindr. The first 200 of you will get 20% off Brilliant’s annual premium subscription. (Video sponsered by Brilliant.org) ▬▬ Papers / Resources ▬▬▬ Colab Notebook: https://colab.research.google.com/dri... Entropy: https://gregorygundersen.com/blog/202... Attractive / Repulsive Forces Gradient: https://jmlr.org/papers/volume23/21-0... t-SNE Parameters distill: https://distill.pub/2016/misread-tsne/ Other great resources: By the t-SNE author: https://lvdmaaten.github.io/tsne/ A good view on probability: https://siegel.work/blog/tSNE/ CalTech tutorial: http://bebi103.caltech.edu.s3-website... Great visuals: https://newsletter.theaiedge.io/p/for... SNE vs T-SNE:   / visualization-method-sne-vs-t-sne-implemen...   t-SNE in raw numpy: https://nlml.github.io/in-raw-numpy/i... t-SNE in raw javascript: https://observablehq.com/@nstrayer/t-... Video by the t-SNE author:    • CVPR18: Tutorial: Part 1: Interpretab...   Image Sources: Perplexity image: https://stats.stackexchange.com/quest... ▬▬ Support me if you like 🌟 ►Link to this channel: https://bit.ly/3zEqL1W ►Support me on Patreon: https://bit.ly/2Wed242 ►Buy me a coffee on Ko-Fi: https://bit.ly/3kJYEdl ►E-Mail: [email protected] ▬▬ Used Music ▬▬▬▬▬▬▬▬▬▬▬ Music from #Uppbeat (free for Creators!): https://uppbeat.io/t/sulyya/weather-c... License code: ZRGIWRHMLMZMAHQI ▬▬ Used Icons ▬▬▬▬▬▬▬▬▬▬ All Icons are from flaticon: https://www.flaticon.com/authors/freepik ▬▬ Timestamps ▬▬▬▬▬▬▬▬▬▬▬ 00:00 Intro 00:30 Manifold learning 02:40 Relevant Papers & Agenda 03:25 Stochastic Neighbor Embedding (SNE) 03:56 Pairwise distances 04:35 Distance to Probability 06:06 Conditional Probability Math 07:05 Adjustment of Variance 08:20 Perplexity 09:55 How to find the variance 11:15 KL-divergence 12:55 Shepard Diagram 13:15 Gradient and it's interpretation 14:15 N-body simulation 14:35 Full SNE Algorithm 15:15 t-distributed Stochastic Neighbor Embedding (t-SNE) 15:28 Crowding Problem and how to solve it 17:58 Gaussian vs. Student's t Distribution 19:21 Symmetric Probabilities 20:35 Early Exaggeration 22:50 SNE vs. t-SNE 23:08 Brilliant.org Sponsoring 24:14 Code 27:15 Distill.pub Blogpost 27:49 Barnes-Hut t-SNE 29:54 Comparison 31:06 Outro ▬▬ My equipment 💻 Microphone: https://amzn.to/3DVqB8H Microphone mount: https://amzn.to/3BWUcOJ Monitors: https://amzn.to/3G2Jjgr Monitor mount: https://amzn.to/3AWGIAY Height-adjustable table: https://amzn.to/3aUysXC Ergonomic chair: https://amzn.to/3phQg7r PC case: https://amzn.to/3jdlI2Y GPU: https://amzn.to/3AWyzwy Keyboard: https://amzn.to/2XskWHP Bluelight filter glasses: https://amzn.to/3pj0fK2