K-Means Clustering From Scratch in Python (Mathematical)

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  • Опубликовано: 1 окт 2024

Комментарии • 22

  • @pitaeata8493
    @pitaeata8493 Год назад +5

    this is great, thank you. it feels good to understand something and be a little closer to understanding machine learning or how to use it properly.

  • @rezaaminafshar
    @rezaaminafshar Месяц назад

    Hi, thanks for your comprehensive explanation.
    I want to use cosine distance as metric instead of Euclidean distance. could you please guide me?
    shoud we just change the part of code which calcaulates Euclidean distance or also other changes need?

  • @neevpenkar4955
    @neevpenkar4955 2 месяца назад

    Beautiful Video!
    If I plan to reuse this code, is this code licensed by you (or anybody else)?. If I reuse it I will post a link to this video but I wanted to be on the safer side!

  • @SeziManuhutu
    @SeziManuhutu 7 месяцев назад

    your explanation is great. but i want to ask, what if we want to know what data is move to different cluster. like at first the data is in 0 cluster but then after that it's move to the other group. how do we know the number of data that is move to another cluster?

  • @arnaldocosta3233
    @arnaldocosta3233 9 дней назад

    Thanks!

  • @philtoa334
    @philtoa334 Год назад +1

    Thx_.

  • @Larzsolice
    @Larzsolice Год назад +1

    I take random points from my data as initial centroids, less computations since you only need the set a random integers for indices.

    • @bibekmaharjan8969
      @bibekmaharjan8969 11 месяцев назад

      Can you share the code for it

    • @Larzsolice
      @Larzsolice 11 месяцев назад

      @bibekmaharjan8969 not sure how here, but the Python random package has a random.choice() or something like that. You can use the data points as the iterable and choose k of them randomly like that.

    • @bibekmaharjan8969
      @bibekmaharjan8969 10 месяцев назад

      @@Larzsolice alright. Thanks a ton

  • @bijayamanandhar3890
    @bijayamanandhar3890 10 месяцев назад

    It's a great tutorial. Beside everything, I just didn't understand why and how it was assumed to have 3 centroids for the example dataset where as you assumed the dataset has no label (unsupervised). Appreciate if you can elaborate. Thanks,

    • @NeuralNine
      @NeuralNine  10 месяцев назад +3

      The number of centroids is the same as the number of clusters. You can either just pick one or you can use techniques to find the "optimal" or at least a good number of clusters. I have a video about this on my channel.

  • @linusolmin9313
    @linusolmin9313 4 месяца назад

    Thank you very much!

  • @Ali110.69
    @Ali110.69 7 месяцев назад

    Hello, I had a question, I wanted to know if I want to work in machine learning or data science, I must use Anaconda and Jumper Lab or can I use Pycharm? I asked this question to many people and they said I should work in Jupyter Lab I can't get along with its environment. I can work inside pycharm or vscode. Your answer can help me a lot. Thank you

    • @PalakGrover-q1u
      @PalakGrover-q1u 6 месяцев назад +1

      Better use VS code to have a JN architecture, and if it creates issues, you may use Pycharm!

    • @sekiro_19
      @sekiro_19 5 месяцев назад +1

      use Jupiter notebook

  • @Hickssama
    @Hickssama 6 месяцев назад

    Thank you sir

  • @aravindputtapaka5147
    @aravindputtapaka5147 Год назад

    I want a python code to convert handwritten image into plain text with accurate i have tried buti didnt got you can try it and show it me sir and plz respond to this comment bcz i am searching for this very curiosly...

    • @AnmolKumar-so8lh
      @AnmolKumar-so8lh 6 месяцев назад

      use OCR(optical charcter recognation) for that using ocr you can extract text from the image

  • @AlexandLupand
    @AlexandLupand 11 месяцев назад

    I'm glad I found this tutorial!

  • @tcgvsocg1458
    @tcgvsocg1458 Год назад

    really interesting

  • @slsushanth
    @slsushanth Год назад +1

    hi i am getting this error can you tell how to solve it
    ValueError: 'c' argument has 200 elements, which is inconsistent with 'x' and 'y' with size 100.