Lecture 3 'k-nearest neighbors' -Cornell CS4780 SP17

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The lecture starts at 2:00!
Amazing explanation on how to pick the right algorithm for your dataset 27:10 otherwise cause bad ML choices!
The lecture starts to approach the k-NN algorithm at 36:00 (before it's about
the training, validation, and test set and about the minimazing
the expected error).

alexenax

your lectures aren't boring at all!!!

ehfo

“When you watch these from bed, they get boring”: sorry Professor, I’m rewatching this class the fifth time and it’s NEVER bored me

Every time I rewatch, I get new appreciation for a new subtlety of the things you say.

It’s gotten to the point that I kinda imitate you when I’m interviewing with companies. In my interviews, it kinda takes the pressure off when I just think of it as your class and me explaining what’s taught in class

sachinpaul

I raise my hand unconciously when you say "Raise your hand if you understood.". Best lectures ever!

omalve

I took a grad-level class in machine learning and got an A, but only now do I realize how crappy my professor was and how little I actually understood. I am really glad I am able to view these lectures for free. Thank you, Dr.Weinberger!

jachawkvr

at 39 minutes Prof. Weinberger said "raise your hand if that makes sense" I actually did !! super high quality content here. That's the level of engagement being created across the world. Respect from India !!

gurdeeepsinghs

These videos help people from other countries which for some reason can't have access to a get a degree in machine learning., ...In my case now I know exactly why I should not split the data randomly with the datasets that I use at my work, thanks so much.

abimaeldominguez

This lecturer has tremendous charisma!

sekfook

Want to get started on some machine learning studying and this is great! Easy to watch while performing menial tasks at work and I can review anything I have questions on at home. Having the notes available to read from ahead of time and then look at during and after the video is tremendous for understanding, thank you very much for providing everyone with such a great font of knowledge.

randajer

Professor Weinberger,
I have taken two graduate-level courses in ML, and I believed I had an understanding until I started your course at eCornell. Man, Build your University! I’m speechless about the level of quality of your lectures! Thank you!

jorgebetancourt

I just finished my first semester studying Data Science and today was supposed to be my first day of holidays, yet I have already watched three of the lectures and still going on. I knew how to apply some of the algorithms in R, but knowing the intuition behind them makes it much more clearer. Thank you professor Weinberger for the amazing content.

styl

Thank you for speaking to the assumptions associated with different models and the chaos of data in the real world.

TrentTube

thanks for the lessons and especially providing coursework, notes, and exams

nolancao

I was looking for an answer that was quite technical in another video but I got hooked. Thank you so much for providing such great knowledge.

Karim-nqbe

Thanks for the lecture! The party game example is really insightful and one that you for sure remember in the future. I also appreciate the jokes a lot, they make the lectures highly engaging!

Oscar-ipys

Many thanks for the systematic presentation of ML. You make it so easy to follow the subject.

vieacademy

Excellent intuition on why validation sets are needed: 13:20

anmolagarwal

This series of lectures brought back my love of learning

pranavhegde

My uncle recommended me this channel. Very very very great class!!!

luq

Welcome to 2020 where your entire college semester is done from your bedroom. :D

meenakshisarkar

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