Machine Learning: Maximum Likelihood Estimation

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  • Опубликовано: 13 дек 2024

Комментарии • 25

  • @alin50248
    @alin50248 11 месяцев назад +4

    Well explained with the proper formal notations that is rare to be seen, good job

  • @Dextro007
    @Dextro007 2 года назад +5

    Very Informative and well presented. I do enjoy such theoretical content. Hope you continue making such videos.

    • @borismeinardus
      @borismeinardus  2 года назад

      I‘m really glad you enjoyed it! I‘ll do my best to produce content that you guys enjoy ☺️ This will hopefully also include more theoretical content.

  • @neurosync_x
    @neurosync_x Месяц назад

    Great work! I'd look forward to a video on Bayesian parameter estimation

  • @adityasonale1608
    @adityasonale1608 10 месяцев назад

    very good explaination, keep posting more content like this

  • @KaneRylander
    @KaneRylander 7 месяцев назад

    I have a good understanding of the end goal of choosing a distribution for each independent observation (3:10), however I am a bit confused on why this works. If we are really choosing a distribution for one observation, wouldn't this just be a delta function since it has a 100% chance of theta fitting the datapoint exactly at that point and a 0% chance elsewhere? It seems like we are almost choosing the standard deviation for the function. Apologies, I would just like to fully understand the process.

  • @GeorgeDole
    @GeorgeDole 8 месяцев назад

    Many thanks for this succinct explanation.

  • @suindude8149
    @suindude8149 Год назад

    Choosing the most likelihood estimation over estimators would be a good choice by forming a Best fit Chi squared model.

    • @borismeinardus
      @borismeinardus  Год назад

      Not quite sure what you mean 🥸

    • @suindude8149
      @suindude8149 Год назад

      @@borismeinardus the list of estimators and the covariance of best fit by normal distribution....in a factory.

  • @im_insaf
    @im_insaf 10 месяцев назад

    @2:07 It should be Parametric form?

  • @ashraygupta7255
    @ashraygupta7255 Год назад

    Damn you teach so well and surprisingly look so good too

  • @subhobratamukharjee1783
    @subhobratamukharjee1783 3 года назад +3

    yes please the video on bayesian parameter estimation also

  • @subhobratamukharjee1783
    @subhobratamukharjee1783 3 года назад

    Again a great video Thanks

  • @Nailartco
    @Nailartco 2 года назад

    You are amazing!

  • @furo.v
    @furo.v 9 месяцев назад +1

    I'd recommend adding captions. It's hard to understand what's being said.

  • @emirbfitness
    @emirbfitness 3 месяца назад

    Nice

  • @-realfoodbro-
    @-realfoodbro- 2 года назад +1

    Do you study at TU Berlin ? 😂