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

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  • Опубліковано 4 гру 2024

КОМЕНТАРІ • 8

  • @DeepFindr
    @DeepFindr  9 місяців тому

    To try everything Brilliant has to offer-free-for a full 30 days, visit brilliant.org/DeepFindr​. The first 200 of you will get 20% off Brilliant’s annual premium subscription.

  • @chemicalengineeringfriends217
    @chemicalengineeringfriends217 8 місяців тому +1

    Great videos! Looking forward to other parts :)

  • @王恺风
    @王恺风 2 місяці тому

    I really enjoy this video! It is so concise, comprehensive and beautiful! And thanks a lot for so many useful links for further learning.

  • @maheshsonawane8737
    @maheshsonawane8737 21 день тому

    It is magnificent video, after understand math and concept behind TSNE, then u can clear ur concept here thoroughly here in this video. 🌟🌟🌟🌟

  • @clairenajjuuko7664
    @clairenajjuuko7664 9 місяців тому +1

    Great video. looking forward to the UMAP video. Will you also be doing something on FAMD?

    • @DeepFindr
      @DeepFindr  9 місяців тому

      Thanks! So far only UMAP is planned but maybe more methods will be added in the future :)

  • @lucapalese475
    @lucapalese475 9 місяців тому

    Really nice! I will read those papers , I guess the backprop is more complex with the t-distribution

    • @DeepFindr
      @DeepFindr  9 місяців тому

      Actually it should be easier because the distribution has an easier function