Linear Regression Mathematical Intuition

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  • Опубліковано 23 лип 2024
  • Simple linear regression is a statistical method that allows us to summarize and study relationships between two continuous (quantitative) variables: One variable, denoted x, is regarded as the predictor, explanatory, or independent variable.
    #LinearRegressionMaths
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КОМЕНТАРІ • 23

  • @suchha8698
    @suchha8698 5 років тому +8

    Hi Krish, I have read so many blogs about Machine learning and watched so many channels and videos on you tube.. But i could not find complete information for what i was searching.. Now my search ends here.. I stopped looking at other sites these days. Lucky that i found your channel.. May god bless you. You are doing a great job!!

  • @MAKExplorer
    @MAKExplorer 3 роки тому +1

    One of the best Linear Regression explanation I have seen till today,Thanks Krish!

  • @nehasaroha2505
    @nehasaroha2505 4 роки тому +1

    By far this is the best explanation that I have come across for these concepts. Thanks so much for doing what you are doing Krish.

  • @naveeng2904
    @naveeng2904 4 роки тому +1

    Thanks Krish! It was amazing tutorial about the math behind the Linear Regression .I was trying hard to understand the concept behind it and you made my life easier .Very much appreciated for your help and for your channel! God bless you !

  • @ga43ga54
    @ga43ga54 5 років тому +3

    Thank you so much for this video!!! This question was asked to me in my interview, really helpful!!! 😀

  • @louerleseigneur4532
    @louerleseigneur4532 3 роки тому

    Thanks Krish

  • @vishtalks695
    @vishtalks695 4 роки тому

    Awesome

  • @junaideqbal2383
    @junaideqbal2383 4 роки тому

    nice explenation.

  • @ga43ga54
    @ga43ga54 5 років тому +1

    Can you also please give an explanation on stochastic gradient decent. Your content is helping me learn alot!!! Thank you Krish!

  • @rajijivpandeylko
    @rajijivpandeylko 4 роки тому

    krish , really informative video, but the links for implementaion not found

  • @Neuraldata
    @Neuraldata 4 роки тому

    Krish, can u make a video on finding the intersection point using gradient descent...as in this video we got to know about finding of slope(m).

  • @nishitnishikant8548
    @nishitnishikant8548 3 роки тому

    Great video and you have put in a very simple way. Needed to clarify this about convergence theorem: should we use partial derivative of J wrt to m, right? But in the video it is partial derivative of m wrt to m(which would be 1). Pls clarify

  • @swaruppanda2842
    @swaruppanda2842 4 роки тому

    least sqr estimator and cost function are they same or different? Can u plz confirm

  • @nott__aceu4857
    @nott__aceu4857 3 роки тому

    can someone link those previous videos that he is mentioning earlier

  • @thealgorithm7633
    @thealgorithm7633 4 роки тому

    How it is assuming the m value?

  • @masked_women1
    @masked_women1 Рік тому

    hi, p;lease guide me towards all previous videos of this course

  • @harshkanumuri3977
    @harshkanumuri3977 3 роки тому

    Please!! someone explain the cost function equation , i dont understand it

  • @rohitkamble1737
    @rohitkamble1737 3 роки тому

    How to calculate RMSE for linear regression?

  • @PremKumar-ws1br
    @PremKumar-ws1br 3 роки тому

    Sir i think videos are not in order than how can i learn since u r explain ation is superb plz say sir

  • @ga43ga54
    @ga43ga54 5 років тому

    In cost function ,why did you take the value of 1/2? and why not some other value?

    • @krishnaik06
      @krishnaik06  5 років тому +1

      Hi we usually say this function as root mean square error function. We can remove 1/2 then it will be call absolute mean error

    • @ga43ga54
      @ga43ga54 5 років тому

      Can we take a square root instead of 1/2 ? Is that a possibility?

  • @chaitanyamallepudi3531
    @chaitanyamallepudi3531 4 роки тому

    Regression vs classification which one to choose! Can be found in
    medium.com/@raghusrinivas1996/regression-or-classification-487600b932c0