Kilian Weinberger
Kilian Weinberger
  • Видео 41
  • Просмотров 1 489 212
The DBSCAN Clustering Algorithm Explained
DBSCAN has become one of my favorite clustering algorithms.
The original paper is here: www.dbs.ifi.lmu.de/Publikationen/Papers/KDD-96.final.frame.pdf
(This video is part of the CS4780 Machine Learning Class.)
Просмотров: 3 644

Видео

CS4780 Transformers (additional lecture 2023)
Просмотров 7 тыс.Год назад
A brief explanation of the Transformer Architecture used in GPT-3, ChatGPT for language modelling. (Uploaded here, for those who missed class due to the unusually nice weather :-) )
On the Importance of Deconstruction in Machine Learning Research
Просмотров 7 тыс.3 года назад
This is a talk I gave in December 2020 at the NeurIPS Retrospective Workshop. I explain why it is so important to carefully analyze your own research contributions through the story of 3 recent publications from my research group at Cornell University. In all three cases did we first invent something far more complicated, only to realize that the gains could be attributed to something far simpl...
Machine Learning Lecture 18 "Review Lecture II" -Cornell CS4780 SP17
Просмотров 11 тыс.4 года назад
Machine Learning Lecture 18 "Review Lecture II" -Cornell CS4780 SP17
In-class Kaggle Competition in less than 5 Minutes
Просмотров 12 тыс.5 лет назад
The Fall 2018 version of CS4780 featured an in-class Kaggle competition. The stuents had 3 weeks to beat my submission, for which I only had 5 minutes. Some students challenged me to show a screencast of me actually training and uploading the model in time, so here you go. Happy Xmas.
Machine Learning Lecture 22 "More on Kernels" -Cornell CS4780 SP17
Просмотров 23 тыс.6 лет назад
Lecture Notes: www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote13.html www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote14.html
Machine Learning Lecture 37 "Neural Networks / Deep Learning" -Cornell CS4780 SP17
Просмотров 15 тыс.6 лет назад
Lecture Notes: www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote20.pdf
Machine Learning Lecture 36 "Neural Networks / Deep Learning Continued" -Cornell CS4780 SP17
Просмотров 14 тыс.6 лет назад
Lecture Notes: www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote20.pdf
Machine Learning Lecture 35 "Neural Networks / Deep Learning" -Cornell CS4780 SP17
Просмотров 21 тыс.6 лет назад
Machine Learning Lecture 35 "Neural Networks / Deep Learning" -Cornell CS4780 SP17
Machine Learning Lecture 34 "Boosting / Adaboost" -Cornell CS4780 SP17
Просмотров 17 тыс.6 лет назад
Lecture Notes: www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote19.html
Machine Learning Lecture 33 "Boosting Continued" -Cornell CS4780 SP17
Просмотров 17 тыс.6 лет назад
Lecture Notes: www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote19.html
Machine Learning Lecture 31 "Random Forests / Bagging" -Cornell CS4780 SP17
Просмотров 46 тыс.6 лет назад
Lecture Notes: www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote18.html If you want to take the course for credit and obtain an official certificate, there is now a revamped version (with much higher quality videos) offered through eCornell ( tinyurl.com/eCornellML ). Note, however, that eCornell does charge tuition for this version.
Machine Learning Lecture 21 "Model Selection / Kernels" -Cornell CS4780 SP17
Просмотров 28 тыс.6 лет назад
Lecture Notes: www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote11.html www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote12.html
Machine Learning Lecture 32 "Boosting" -Cornell CS4780 SP17
Просмотров 35 тыс.6 лет назад
Lecture Notes: www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote19.html
Machine Learning Lecture 30 "Bagging" -Cornell CS4780 SP17
Просмотров 26 тыс.6 лет назад
Lecture Notes: www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote18.html
Machine Learning Lecture 29 "Decision Trees / Regression Trees" -Cornell CS4780 SP17
Просмотров 45 тыс.6 лет назад
Machine Learning Lecture 29 "Decision Trees / Regression Trees" -Cornell CS4780 SP17
Machine Learning Lecture 28 "Ball Trees / Decision Trees" -Cornell CS4780 SP17
Просмотров 31 тыс.6 лет назад
Machine Learning Lecture 28 "Ball Trees / Decision Trees" -Cornell CS4780 SP17
Machine Learning Lecture 27 "Gaussian Processes II / KD-Trees / Ball-Trees" -Cornell CS4780 SP17
Просмотров 30 тыс.6 лет назад
Machine Learning Lecture 27 "Gaussian Processes II / KD-Trees / Ball-Trees" -Cornell CS4780 SP17
Machine Learning Lecture 26 "Gaussian Processes" -Cornell CS4780 SP17
Просмотров 72 тыс.6 лет назад
Machine Learning Lecture 26 "Gaussian Processes" -Cornell CS4780 SP17
Machine Learning Lecture 25 "Kernelized algorithms" -Cornell CS4780 SP17
Просмотров 14 тыс.6 лет назад
Machine Learning Lecture 25 "Kernelized algorithms" -Cornell CS4780 SP17
Machine Learning Lecture 24 "Kernel Support Vector Machine" -Cornell CS4780 SP17
Просмотров 19 тыс.6 лет назад
Machine Learning Lecture 24 "Kernel Support Vector Machine" -Cornell CS4780 SP17
Machine Learning Lecture 23 "Kernels Continued Continued" -Cornell CS4780 SP17
Просмотров 15 тыс.6 лет назад
Machine Learning Lecture 23 "Kernels Continued Continued" -Cornell CS4780 SP17
Machine Learning Lecture 20 "Model Selection / Regularization / Overfitting" -Cornell CS4780 SP17
Просмотров 22 тыс.6 лет назад
Machine Learning Lecture 20 "Model Selection / Regularization / Overfitting" -Cornell CS4780 SP17
Machine Learning Lecture 19 "Bias Variance Decomposition" -Cornell CS4780 SP17
Просмотров 48 тыс.6 лет назад
Machine Learning Lecture 19 "Bias Variance Decomposition" -Cornell CS4780 SP17
Machine Learning Lecture 17 "Regularization / Review" -Cornell CS4780 SP17
Просмотров 17 тыс.6 лет назад
Machine Learning Lecture 17 "Regularization / Review" -Cornell CS4780 SP17
Machine Learning Lecture 16 "Empirical Risk Minimization" -Cornell CS4780 SP17
Просмотров 27 тыс.6 лет назад
Machine Learning Lecture 16 "Empirical Risk Minimization" -Cornell CS4780 SP17
Machine Learning Lecture 15 "(Linear) Support Vector Machines continued" -Cornell CS4780 SP17
Просмотров 27 тыс.6 лет назад
Machine Learning Lecture 15 "(Linear) Support Vector Machines continued" -Cornell CS4780 SP17
Machine Learning Lecture 14 "(Linear) Support Vector Machines" -Cornell CS4780 SP17
Просмотров 44 тыс.6 лет назад
Machine Learning Lecture 14 "(Linear) Support Vector Machines" -Cornell CS4780 SP17
Machine Learning Lecture 13 "Linear / Ridge Regression" -Cornell CS4780 SP17
Просмотров 34 тыс.6 лет назад
Machine Learning Lecture 13 "Linear / Ridge Regression" -Cornell CS4780 SP17
Machine Learning Lecture 12 "Gradient Descent / Newton's Method" -Cornell CS4780 SP17
Просмотров 47 тыс.6 лет назад
Machine Learning Lecture 12 "Gradient Descent / Newton's Method" -Cornell CS4780 SP17

Комментарии

  • @patrickmesana5942
    @patrickmesana5942 8 дней назад

    Kilian is amazing

  • @Selim-of8gq
    @Selim-of8gq 13 дней назад

    you are like a gift from Nature <3 .

  • @ruiqizhu8946
    @ruiqizhu8946 14 дней назад

    Goat prof

  • @saajanrajak3054
    @saajanrajak3054 19 дней назад

    5:57 - boundary point can be assigned to any one group. but it may change if we restart the dbscan model. does it affect the model?

    • @kilianweinberger698
      @kilianweinberger698 19 дней назад

      Yes, it depends on the order in which we start. That's OK though. After all there isn't a true answer and other algorithms (e.g. K-means) are even more initialization dependent.

  • @Selim-of8gq
    @Selim-of8gq 28 дней назад

    <3

  • @ChenLiu-nc5tg
    @ChenLiu-nc5tg Месяц назад

    This is cool!

  • @Lfmpereira1
    @Lfmpereira1 Месяц назад

    Amazing lecture.

  • @MarcoGelsomini-r8c
    @MarcoGelsomini-r8c Месяц назад

    34:52 very interesting point!

  • @amorphous8826
    @amorphous8826 Месяц назад

    👍

  • @szaybhattacharya1022
    @szaybhattacharya1022 Месяц назад

    I will start my machine learning journey, I have the knowledge of stat , calculus, linear algebra.Should I follow this series?. From comments it seems this is a very very good lecture series. Or this would be too advance for a newbie like me?

  • @adosar7261
    @adosar7261 Месяц назад

    At 39:53 the example seems a little bit off to me. I would expect Newton's method to converge in a single step (the function looks like a quadratic).

    • @leviiida9967
      @leviiida9967 12 дней назад

      The second order Taylor's approximation gives the polynomial equation of the parabola that approximates the function at a point .Here the function is the small parabola and the approximation is the other wider parabola, Newton's method minimises the wider parabola, that's why it will just shoot off in a single step

    • @adosar7261
      @adosar7261 11 дней назад

      @leviiida9967 Doesn't the approximation looks a bit off? I understand the purpose of the drawing, i.e. that we bounce back and forth. It just felt "too contrived", that is if we construct the second order approximation it would be steeper.

  • @amorphous8826
    @amorphous8826 Месяц назад

    👍

  • @amorphous8826
    @amorphous8826 Месяц назад

    👍

  • @srisaisubramanyamdavanam9912
    @srisaisubramanyamdavanam9912 Месяц назад

    compression comparison for cross entropy is just damn good....

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thanks a lot. Wished I could have attended 'ML for Data Science' as well

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thank you Professor !!!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    "If you can't read my handwriting, you are not alone" :)

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thank you Sir !!!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thanks a lot !!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thank you !!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thanks a lot !!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thanks a lot Sir !!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thanks !!!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thanks !!!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thank you Professor !!!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    The time watching these lectures passes in no time !! Thanks, Professor!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 Месяц назад

    Thank you for the amazing Lecture !!!

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 2 месяца назад

    Thank you so much Sir !!!

  • @shashanksharma1498
    @shashanksharma1498 2 месяца назад

    He is a fantastic teacher. And all the energetic teaching has given him a bad throat.

  • @jandrzej1264
    @jandrzej1264 2 месяца назад

    I like your way of teaching more than Andrew or anyone else, cause they assume students or anyone watching is at least tiny intelligent, which just isnt the case. After all we are all just stupid, except for few people, or that one kid in class

  • @jandrzej1264
    @jandrzej1264 2 месяца назад

    And here i am rewatching this for the 3-th time, cause i didnt take notes. This time i wont make that mistake, i already filled a whole notebook with this. Thanks Kilian, sad there isnt anything more tho

  • @filiprechtorik4938
    @filiprechtorik4938 2 месяца назад

    JULIA

  • @gledguri
    @gledguri 2 месяца назад

    Super cool! Thanks!

  • @lambukushireddy424
    @lambukushireddy424 2 месяца назад

    best lecture on naive bayes.

  • @filthyfillium
    @filthyfillium 2 месяца назад

    in lecture notes there is a spelling error in the concluding summary "week classifier"

  • @thatsharma1066
    @thatsharma1066 2 месяца назад

    lectures so good, kilian on my poster wall. :)

  • @Exhora
    @Exhora 2 месяца назад

    Are the slides for the first part of the class available?

  • @bansaloni
    @bansaloni 3 месяца назад

    I have been watching your lectures for years now. I must say, the style of teaching is the best ! Every-time I need a refresher on some topic, your ML series is the first I think of. Thank you for the amazing content! 😃

  • @filipgaming1233
    @filipgaming1233 3 месяца назад

    wonderful lecture

  • @vocabularybytesbypriyankgo1558
    @vocabularybytesbypriyankgo1558 3 месяца назад

    A Great Beginning..excited for the next

  • @Dragon-Slay3r
    @Dragon-Slay3r 3 месяца назад

    I always tried to help, each time i did the cult took advantage now its their problem, and i dont know if i can help anybody everything has changed since last night

  • @officialstylechild
    @officialstylechild 4 месяца назад

    Raise your hand if that makes sense… crickets… ok moving on!

  • @andreariboni4242
    @andreariboni4242 4 месяца назад

    dead mouse got me

  • @IrfanSaleem541
    @IrfanSaleem541 4 месяца назад

    Prof, record small videos on SVM, SVR and Soft margin SVM, if possible.

  • @05me39
    @05me39 4 месяца назад

    Pure gold. The lectures are excellent. The humor is spot on. Many many thanks.

  • @AakarshNair
    @AakarshNair 4 месяца назад

    wow, you are a good teacher!

  • @daniilzaytsev2040
    @daniilzaytsev2040 4 месяца назад

    Legendary course!

  • @rakinbaten7305
    @rakinbaten7305 4 месяца назад

    I'm curious if someone was actually stealing all the notes

  • @rakinbaten7305
    @rakinbaten7305 5 месяцев назад

    geez does anyone ever wonder what beast of a middle school Killian went to? 37:29

  • @butterChickenAndNaan98
    @butterChickenAndNaan98 5 месяцев назад

    End score tallly: Under-grad = 255 Grad = 310 Grad Won!!