ML estimate of Poisson and Geometric distribution

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  • Опубликовано: 27 окт 2024

Комментарии • 16

  • @furo.v
    @furo.v 8 месяцев назад

    Amazing. This is literally the only video/book/article about MLE that I could understand perfectly! Thanks

  • @shrutijindal6040
    @shrutijindal6040 3 года назад +5

    Your channel is so underrated. Keep it up!

  • @sagaradoshi
    @sagaradoshi 2 года назад +1

    Thanks for the vide..it really helped to understand the concepts. Request you to create a video on MAP estimate of parameters..

  • @amosreagan6833
    @amosreagan6833 Год назад

    THANKS FOR THE PRESENTATION. AM HAPPY THAT I HAD FAILED TO UNDERSATND THIS PART BUT I HAVE NOW FULLY GOTTEN IT. M y only request is that you help always explain it all in English because some of us don't understand the other language and yet you might be explaining the part we are most interested in understanding. thanks

  • @buvanaanand5962
    @buvanaanand5962 8 месяцев назад

    Your way of teaching is good and easily understandable. However, I would like to check with you that the second order differentiation will be taken and it should be less than 0 to confirm that it is a MLE. But here it is not addressing about that. Could you please clarify it?

  • @nbd_08uma_nandan30
    @nbd_08uma_nandan30 2 года назад

    Very Nice explanation mam .

  • @anandiyer5361
    @anandiyer5361 3 года назад

    Very nice...well explained. I'm going to subscribe to the channel. I hope to see more videos here!

    • @anandiyer5361
      @anandiyer5361 3 года назад +1

      Just a suggestion. You might eventually have viewers from other parts of the country, or even across the globe. So, try to use English as the medium throughout.

  • @satheeshkumarvb3470
    @satheeshkumarvb3470 3 года назад +1

    Please teach about basics of ML, AI, and DS, and functions of layers are in NN, CNN, RNN etc.., Mam.

  • @hemakrishnan4533
    @hemakrishnan4533 2 года назад

    Compute ML estimate for the parameter p in the binomial distribution whose
    probability function is
    f(x)=( n) px(1-p)(n-x). x and 1-x are exponents. Mam this is a university question of 2018. Can you please put the solution for this.
    x

  • @jpdan66
    @jpdan66 Год назад +1

    Thanks

  • @nathanielsackey2083
    @nathanielsackey2083 3 года назад

    I wasnt getting how we got the - nT

    • @eduflairktucs7636
      @eduflairktucs7636  3 года назад +1

      You mean -n lamda in poisson distribution?? or can you please mention the specific time..

    • @secretwound4260
      @secretwound4260 7 месяцев назад

      Yes ...can you explain?